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The purpose of this paper is to explore the influence of subsidiary autonomy on subsidiary performance under uncertainty. Based on previous studies, the authors classify subsidiary autonomy into two categories, namely, strategic autonomy and operational autonomy, and investigate the relationships between these two categories of subsidiary autonomy and subsidiary performance under uncertainty.

The sample includes the subsidiaries listed on the Shanghai and Shenzhen Stock Exchanges in China from 2012 to 2015. Ordinary least squares are used to examine the hypotheses.

The results indicate that strategic autonomy is negatively related to subsidiary performance, whereas operational autonomy is positively associated with subsidiary performance. Moreover, uncertainty weakens the negative strategic autonomy-subsidiary performance linkage.

The findings of this study indicate that two categories of subsidiary autonomy (strategic autonomy, operational autonomy) have different effects on subsidiary performance. Moreover, uncertainty moderates the above relationships. This study explores the relationship between subsidiary autonomy and subsidiary performance and provides a useful guidance for the selection of subsidiaries’ management modes.

Quadrotor micro aerial vehicle (MAV) is nonlinear and under actuated plant, and it is difficult to obtain an accurate mathematical model for quadrotor MAV due to uncertainties. The purpose of this paper is to propose one robust control strategy for quadrotor MAV to accommodate system uncertainties, variations, and external disturbances.

The robust control strategy is composed of two self‐organizing interval type‐II fuzzy neural networks (SOIT‐IIFNNs) and one PD controller: the PD controller is adopted to control the attitude and position; one of the SOIT‐IIFNNs is designed to learn the inverse model of quadrotor MAV online; the other SOIT‐IIFNNs is the copy of the former one to compensate for model errors, system uncertainties and external disturbances, both structure and parameters of SOIT‐IIFNNs are tuned online at the same time, and then the stability of the resulting quadrotor MAV closed‐loop control system is proved using Lyapunov stability theory.

The validity of the proposed control method has been verified through real‐time experiments. The experimental results show that the performance of SOIT‐IIFNNs is significantly improved compared with Backstepping‐based controller.

This approach has been used in quadrotor MAV, the controller works well, and it could guarantee quadrotor MAV control system with good performances under uncertainties, variations, and external disturbances.

The proposed SOIT‐IIFNNs controller is interesting for the design of an intelligent control scheme. The main contributions of this paper are: the overall closed‐loop control system is globally stable, demonstrated by Lyapunov stable theory; the tracking error can be asymptotically attenuated to a desired small level around zero by appropriate chosen parameters and learning rates; and the quadrotor MAV control system based on SOIT‐IIFNNs controller can achieve favorable tracking performance.

This paper aims to explore the mechanism underlying the relationship between abusive supervision differentiation (ASD) and team performance. The moderating roles of inter-team and intra-team competitive climate are also examined.

This research collects data from 419 employees and 71 supervisors from hospitals and financial companies in China. Techniques include descriptive statistics and hierarchical multiple regression are applied to analyze the data.

This research finds that (1) team relationship conflict mediated the relationship between ASD and team performance and (2) intra-team competitive climate strengthened the indirect relationship between ASD and team performance through team relationship conflict.

The results indicate that organizations should take measures to minimize the occurrence of abusive supervision. Team leaders should increase self-control and avoid abusing employees. Furthermore, organizations should establish an open and fair reward and punishment system to avoid cutthroat competition.

This study advances our knowledge of how ASD results in poor team effectiveness. This contributes to the literature by identifying team relationship conflict as a mediating mechanism linking the negative association of ASD with team performance. Additionally, competitive climate enriches the individual-focused team-level model of abusive supervision.

This study aims to dispense a concrete and coherent picture on the role of digitalization of accounting information (DOAI) among the small and medium-sized enterprises (SMEs) through a statistically reliable and parsimonious paradigm for procuring the impact of DOAI on sustainable innovation ecosystem (SIE) and public value (PV) generation. With this cue, the geographical scope of this tentative manuscript was framed in SMEs of developing countries.

A three-pronged methodology was disposed in this research, namely, literature review, expert interviews and self-administered survey. Qualitative data was procured from a series of semi-structured in-depth interviews. The quantitative data was drawn on a self-administered survey in which the closed-ended questionnaires were conveniently circulated to a cross-sectional sample of 583 respondents. The data captured from quantitative approach was processed and analyzed via covariance-based structural equation modeling with AMOS 26.0.

The outcomes analysis highlighted that there were significant positive associations between the hypothesized constructs regarding significance and effect size. These interlinks were also partially mediated through the mediation of quality of information on financial reports and SIE.

This research was bounded by geographical provenance emphasis on one country and relative smallness of the data set procured through anonymous survey-based approach drawn from a convenient sample of digitally savvy respondents working in one sub-sector resulted in the reduction in the robustness and generalizability of the observations. Nevertheless, these above-mentioned limitations could thus offer the starting points for novel avenues creation for the future research.

The practitioners would definitely have valuable benefits from in-depth insights on the obtained findings. Concretely, as lifting the degree of understandings on the magnitude of long-term cooperation and superior coordination within the SIE would enable practitioners to enlarge their business viewpoints to better cope with the challenges of complicated business settings, facilitating them to co-create PV for all their key stakeholders through giving priority to implementing DOAI.

Society could benefit from this study if policymakers and the influencers of government focus on innovative features and assure the possible environment for innovation deployment through embarking on introducing policies that would facilitate the digitalization as well as stimulate and incentivize establishing the SIE for PV generation. It would be good for both the SMEs and society when SMEs could thrive in community settings as well as this togetherness.

Unpacking the potential of DOAI has been considered as the promising research avenues that are outlined not only to redress the shortfall in the research stream in relation to the digitalization among SMEs but also provide the right directions for sustainable development among SMEs.

The purpose of this paper is to develop a compressive sensing (CS) algorithm for noisy solder joint imagery compression and recovery. A fast gradient-based compressive sensing (FGbCS) approach is proposed based on the convex optimization. The proposed algorithm is able to improve performance in terms of peak signal noise ratio (PSNR) and computational cost.

Unlike traditional CS methods, the authors first transformed a noise solder joint image to a sparse signal by a discrete cosine transform (DCT), so that the reconstruction of noisy solder joint imagery is changed to a convex optimization problem. Then, a so-called gradient-based method is utilized for solving the problem. To improve the method efficiency, the authors assume the problem to be convex with the Lipschitz gradient through the replacement of an iteration parameter by the Lipschitz constant. Moreover, a FGbCS algorithm is proposed to recover the noisy solder joint imagery under different parameters.

Experiments reveal that the proposed algorithm can achieve better results on PNSR with fewer computational costs than classical algorithms like Orthogonal Matching Pursuit (OMP), Greedy Basis Pursuit (GBP), Subspace Pursuit (SP), Compressive Sampling Matching Pursuit (CoSaMP) and Iterative Re-weighted Least Squares (IRLS). Convergence of the proposed algorithm is with a faster rate O(k*k) instead of O(1/k).

This paper provides a novel methodology for the CS of noisy solder joint imagery, and the proposed algorithm can also be used in other imagery compression and recovery.

According to the CS theory, a sparse or compressible signal can be represented by a fewer number of bases than those required by the Nyquist theorem. The new development might provide some fundamental guidelines for noisy imagery compression and recovering.

The purpose of this study is to measure the financial reporting quality of 38 main countries (regions) in the world from 2000 to 2014.

This paper uses six accounting and auditing indicators to construct a comprehensive index for the measurement of country-level financial reporting quality. To test the validity of the methodology, the index to test institutional impacts on national financial reporting quality is used.

It was found that the results are consistent with the predictions and previous studies. The evidence suggests that the quality measure in this paper is innovative and appropriate and can provide a useful tool for researchers who are concerned with financial reporting quality at the country level.

The study is the first in the literature to use both accounting and auditing data to construct financial reporting quality indicators. The study should help international investors assess investment risks in foreign financial markets so as to make an informed decision. In addition, the diversity of financial reporting practices documented in the paper should prompt market regulators, accounting standard setters and professional accounting bodies to reinforce the efforts on international convergence of accounting and financial reporting standards and practices.

The purpose of this paper is to present a method to accurately forecast the tendency of the gross amount of energy sources consumption of the country and construct a new kind of algorithm for forecasting that synthesizes the advantages of the grey model, Markov chains, and least square method.

With the application of this new algorithm, this paper have forecasted the trend of the gross amount of energy sources consumption of the country and come to the conclusions that the new algorithm is more precise than the grey model. It is proved that the improved grey‐Markov chain algorithm is effective and can be used by authorities to make decision.

It was found that combining the grey model, Markov chains, and least square method, can be a new algorithm for forecasting the trendency of the gross amount of energy sources consumption.

The new algorithm is only suitable for the short‐term forecast.

The grey forecasting method reflects the overall tendency of primitive data sequence of the gross amount of energy source, and the Markov chain forecasting method reflects the effect of the random fluctuation. The least square method reflects the tendency of increase. The new algorithm is more precise than the grey model.

This paper aims to systematically expound the theory and development background of supply chain finance and blockchain, design a railway freight supply chain financial platform based on blockchain, determine the risk management system and business support system of supply chain finance business and analyze the value generated by the combination of supply chain finance business and blockchain.

Investigation and research method; Prototype method; Model method; Value analysis.

The business model integrating supply chain finance and blockchain technology will bring great changes to freight industry. The development of supply chain finance is beneficial to the healthy development of the core participants of railway freight transport business and its upstream and downstream ecosystems. It links commerce, logistics, warehousing and financial services together and builds an industry-integrated ecological service platform through information technology platform and supporting system, taking data as the basis and combining information technology such as blockchain as innovative means.

This paper will provide important reference value for related research. This paper innovatively designs the supply chain financial platform of freight transportation industry-integrating blockchain technology and analyzes its business model, technical system, risk management and control system and value system in detail, which will provide technical support for the innovative reform of freight information technology and realize the stable and high-speed development of freight logistics informationization.

Based on ideal absolute errors and relative errors, a new grey model‐GM^p(1,1) model is presented. The existence problem of its solution is also solved based on a few conditions. Then, MGM^p(1,n) model is presented. These optimized models GM^p(1,n) and MGM^p(1,n) have good anti‐noise property to absolute and relative errors. Examples illustrate that they have very good fitting and forecasting results.

“Poor” information systems are found everywhere. In this paper, a control approach to “poor” information systems, such as social economic systems, is proposed. First, “poor” information processing and SCGM‐model will be discussed. Secondly, we will develop an optimal controller of “poor” information systems.