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The purpose of this paper is to explore financial quality problems, based on the dynamics of the ownership structure, in the privatization process to clarify the internal relation among the ownership’s attribution of the commercial mixed ownership company, the company’s performance and its financial relationships. This paper also examines the mixed ownership enterprise’s potential problems during the development process.

Adopting the single case study method, the authors selected the mixed ownership public company Hubei Sanxia New Building Materials Co., Ltd. (stock code: 600293) to explore, from a privatization perspective, the impact of mixed ownership on financial quality.

The study found that Sanxia experienced tight cash flow and heavy debt burdens due to the privatization and that its controlling shareholders used non-operating income to support Sanxia, thus characterizing the dual role of “the grabbing hand” and “the helping hand.” Sanxia’s privatization process highlighted the volatility of performance, the exception of monetary funds and the existence of accounting fraud rather than the prosperous development of the capital combination.

These findings provided case support that privatization negatively affects the financial quality of the company. Previous studies have indicated that there should be greater focus more on the issue that state-owned shares rebound during the process of privatization and that, with respect to commercial mixed ownership reform of state-owned enterprises, such reform must avoid the passive transfer of corporate control, ensure the fairness of the related transactions, prevent the loss of state-owned assets and preclude the controlling shareholders from seizing interests of listed companies.

The purpose of this paper is to construct a prediction model of three-parameter interval grey number based on kernel and double information domains to expand the modeling object of grey prediction model from interval grey number to three-parameter interval grey number.

First, the study decomposes the grey valued interval into upper and lower cells with the “center of gravity” as the dividing point and defines the upper and lower information domains of the three-parameter interval grey number. Second, it calculates the kernel, the upper and lower information domains of the three-parameter interval grey number. Then, it constructs the prediction model for kernel sequence and upper and lower information domain sequences, respectively. By deducing the time response expressions of “center of gravity”, lower and upper limits of three-parameter interval grey number, a prediction model of three-parameter interval grey number based on kernel and double information domains is obtained.

This paper provides a prediction model of three-parameter interval grey number based on kernel and double information domains, and the example analysis shows that the method proposed in this paper has higher prediction accuracy and practicality.

In this paper, the modeling object of grey prediction model is extended to the three-parameter interval grey number, so it can be used for the prediction of uncertainty problems, such as stock changing trend, temperature and so on.

By decomposing the grey valued interval into upper and lower cells with the “center of gravity” as the dividing point, gives the definition of upper and lower information domains and then obtains a new method for whitening the three-parameter interval grey number.

The purpose of this paper is to construct an unbiased interval grey number prediction model with new information priority for dealing with the jumping errors from difference equation to the differential equation in the prediction model of interval grey number.

First, this study obtains a set of linear equations about the model parameters by taking the minimum error sum of squares between the accumulative sequence and its simulation values as criterion, and solves them on the basis of the Crammer rule. Then, according to the new information priority principle, it selects the last number of the accumulated generation sequence as the initial value and gives the expression of the time response function by the recursive iteration method to establish the interval grey number prediction model.

This paper provides an unbiased interval grey number prediction model with new information priority, and the example analysis shows that the method proposed in this paper has higher prediction precision and practicality.

If there is a better method to whiten the interval grey number, so as to fully tap the grey information contained in it, the accuracy of the model will be higher.

The model proposed in this paper can avoid the error caused by jumping from difference equation to differential equation and make full use of new information. It can be better used in a problem where new information has a great influence on prediction results.

This paper selects the last number of the accumulated generation sequence as the initial value and gives the expression of the time response function by the recursive iteration method. Then, it constructs an unbiased interval grey number prediction model with new information priority.

This article aims to better understand game-based learning teaching practices through an interview with Zack Gilbert, a 6th grade teacher who is incorporating video games Civilization IV (Civ) and Minecraft into his social studies classroom.

This article is based on an interview with Zack Gilbert, regarding his practices and ideas toward using video games to facilitate learning.

In this interview, he shared his journey exploring teaching practices and experiences applying Civ and Minecraft to social studies class, which may serve as an example for other teachers.

The pioneering and successful experiences of Zack Gilbert may offer an example or insights for other teachers who intend to incorporate video games into their classrooms.

This paper aims to examine alliance governance at different hierarchical levels.

The data is collected from both top-level and operating-level managers in 286 strategic alliances in China (a total of 572 managers). Hierarchical moderated regression models are adopted to test the hypotheses and two-stage regression analyzes are used to correct for endogeneity.

This paper finds that relational governance has a greater impact on alliance performance than contract utilization at the top level. Furthermore, the simultaneous use of relational governance at the top and operating levels have a detrimental impact on alliance performance. Finally, top-level contract utilization has a negative interaction with operating-level relational governance but a positive interaction with operating-level contract utilization.

First, the cross-sectional nature of the data collection approach provides only a snapshot of how each type of governance mechanism and its interactions affect alliance performance. Second, the sample is limited to firms located in emerging markets.

Managers should realize that the effectiveness of contract and relational governance mechanisms varies across different management levels and they should be cautious about the cross-level governance mechanism alignment.

This study advances the interfirm governance literature in that this paper examined alliance governance at different hierarchical levels and provides new insights into the ongoing debate on whether the contract and relational governance mechanisms function as complements or substitutes by exploring the governance alignment across different alliance hierarchies.

This paper mainly aims to deal with the problems of uncertainties including modelling errors, unknown dynamics and disturbances caused by load mutation in control of permanent magnet synchronous motor (PMSM).

This paper proposes an enhanced speed sensorless vector control method based on an active disturbance rejection controller (ADRC) for a PMSM. First, a state space model of the PMSM is obtained for the field orientation control strategy. Second, a sliding mode observer (SMO) based on back electromotive force (EMF) is introduced to replace the encode to estimate the rotor flux position angle and speed. Third, an infinite impulse response (IIR) filter is introduced to eliminate high frequency noise mixed in the output of the sliding mode observer. In addition, a speed control method based on an extended state observer (ESO) is proposed to estimate and compensate for the total disturbances. Finally, an experimental set-up is built to verify the effectiveness and superiority of the proposed ADRC-based control method.

The comparative experimental results show that the proposed speed sensorless control method with the IIR filter can achieve excellent robustness and speed tracking performance for PMSM system.

An enhanced sensorless control method based on active disturbance rejection controller is designed to realize high precision control of the PMSM; the IIR filter is used to attenuate the chattering problem of traditional SMO; this method simplifies the system and saves the total cost due to the speed sensorless technology.

The use of sensorless can reduce costs and be more beneficial to actual industrial application.

The proposed enhanced speed sensorless vector control method based on an ADRC with the IIR filter enriches the control method of PMSM. It can ameliorate system robustness and achieve excellent speed tracking performance.

High-ductility cementitious composites (HDCC) have an excellent crack controlled capacity and corrosion resistance capacity, which has a promising application in structure engineering under harsh environment. The purpose of this study is to explore the corrosion mechanism of steel bar in HDCC.

Intact and the pre-cracked HDCC specimens under the coupled action of different dry–wet cycles and chloride attack were designed, and intact normal concrete (NC) was also considered for comparison. Corrosion behavior of a steel bar embedded in HDCC was analyzed by an electrochemical method, a chloride permeability test and X-ray computed tomography.

Steel corrosion probability is related to the chloride permeability of the HDCC cover, and the chloride permeability resistance of HDCC is better than that of NC. Besides, crack is the key factor affecting the corrosion of steel bars, and the HDCC with narrower cracks have a lower corrosion rate. Slight pitting occurs at the crack tips. In addition, the self-healing products and corrosion products fill up the cracks in HDCC, preventing the external aggressive ions from entering and thereby decreasing the steel corrosion rate.

HDCC has a superior corrosion resistance than that of NC, effects of variable crack width on corrosion behavior of steel bar in HDCC under the coupled actions of different dry–wet cycles and chloride attack are investigated, which can provide the guide for the design application of HDCC material in structure engineering exposed to marine environment.

In an integrated circuit (IC) substrate, more fillers, including talcum powder and aluminium hydroxide, are added, which leads to much higher rigidity and hardness compared with a traditional printed circuit board. However, the micro drilling of IC substrates is harder. This paper aims to test the drilling process of IC substrates to improve the drilling process and the micro hole quality.

Substrate drilling by a micro drill with 0.11-mm diameter was used under several drilling conditions. The influence of drilling conditions on the drilling process was observed. Drilling forces, drill wear and micro hole quality were also studied.

The deformation circle around holes, hole location accuracy, bugle hole and burrs were the major defects of micro holes that were observed during the drilling of the substrate. Reducing the drilling force and drill wear was the effective way to improve hole quality.

The technology and manufacturing of IC substrates has been little investigated. Research data on drilling IC substrates is lacking. The micro hole quality directly affects the reliability of IC substrates. Thus, improving the drilling technology of IC substrates is very important.

This research proposes and examines a theoretical model grounded in anthropomorphism theory considering the curvilinear and linear relationships between service robot anthropomorphism and consumer usage intention and explores the mediating effect of perceived risk.

To examine the developed model, two complementary studies are designed. In Study 1, multi-time data of 511 participants show that service robot anthropomorphism inverts U-shaped (curvilinear) relationship on consumer usage intention and perceived risk mediates this curvilinear relationship. In Study 2, multi-source data of 460 volunteers are used to confirm the findings of Study 1 and examine that consumer empathy moderates the complex nonlinear effect of service robot anthropomorphism on perceived risk, and the indirect curvilinear effect of service robot anthropomorphism on consumer usage intention through perceived risk.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

Although research on how the downstream calculations of a patent’s profit potential influence invention renewal decisions is extensive, the impact of the upstream knowledge creation stages is overlooked. The purpose of this study is to address this theoretical vacuum by examining the intra-organizational configuration of knowledge networks and collaboration networks.

The data consist of 491 global pharmaceutical firms that patent in the USA. Drawing on patent records, the authors simultaneously construct intra-organizational knowledge networks and collaboration networks and identify network cohesion features (i.e. local and global). The authors employ panel fixed-effects models to test the hypotheses.

The results show that local knowledge cohesion and local social cohesion decrease invention renewals, while global knowledge cohesion and global social cohesion increase renewals. Moreover, the marginal effects of local and global social cohesion are stronger than those of local and global knowledge cohesion, respectively.

The hypotheses are tested using the pharmaceutical industry as a research setting, which limits the generalizability of our findings. In addition, potential formal and informal contingencies are not considered.

Despite its limitations, this study provides valuable implications. First, managers are cautioned against the adverse effects of local cohesion structures on invention renewal. Second, firms can dynamically adjust their local and global network configuration strategies to harmonize the generation of valuable inventions and the retention of good ideas.

Complementary to previous research that focused on inventions’ performance feedback, this study delves into upstream knowledge creation stages to understand invention renewals.