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The purpose of this paper is to determine the principal organisational cultural dimensions that affect levels of post-merger integration (PMI) in Chinese acquisitions in Germany and to explore the relationship of these specific organisational cultural dimensions and levels of integration.

Data set were collected using a structured questionnaire given to Chinese and German managers and employees, who implemented/were responsible for the PMI in 12 Chinese acquisitions in Germany. A total of 120 questionnaires were distributed and there were 67 respondents, corresponding to a response rate of about 56 per cent. Principal components analysis, one-way ANOVA and bi-variate Spearman’s correlation were applied to analyse the data.

Findings revealed that five organisational cultural dimensions (i.e. adaptability, consistency, involvement, balance and flexibility) were extracted to be the primary indicators affecting levels of integration in Chinese reverse mergers and acquisitions (M&As) in the German market. Further, adaptability emerged as the only predictor with a significant negative implication on predicting the degree of PMI that Chinese investors would initiate to integrate their acquired German subsidiaries.

This study is one of the few studies to consider the specific organisational cultural dimensions affecting the integration levels of reverse M&As and is the first study, to the best of our knowledge, to explore the correlations of specific corporate cultural dimensions and integration levels in emerging multinational enterprises’ reverse M&As through quantitative research.

This paper aims to provide a symplectic conservation numerical analysis method for the study of nonlinear LC circuit.

The flux linkage control type nonlinear inductance model is adopted, and the LC circuit can be converted into the Hamiltonian system by introducing the electric charge as the state variable of the flux linkage. The nonlinear Hamiltonian matrix equation can be solved by perturbation method, which can be written as the sum of linear and nonlinear terms. Firstly, the linear part can be solved exactly. On this basis, the nonlinear part is analyzed by the canonical transformation. Then, the coefficient matrix of the obtained equation is still a Hamiltonian matrix, so symplectic conservation is achieved.

Numerical results reveal that the method proposed has strong stability, high precision and efficiency, and it has great advantages in long-term simulations.

This method provides a novel and effective way in studying the nonlinear LC circuit.

The purpose of this paper is to propose cuckoo optimization algorithm (COA)-based back propagation neural network (BPNN) to reduce the effect of the nonlinearities presented in laser triangulation displacement sensors. The 3D positioning and posture sensor allows access to the third dimension through depth measurement; the performance of the sensor varies according to the level of nonlinearities presented in the system, which leads to inaccuracies in measurement.

While applying optimization approach, the mathematical model and the relationship between the key parameters in the laser triangulation ranging and the indexes of the measuring system were analyzed.

Based on the performance of the parametric optimization method, the measurement repeatability reached 0.5 µm with an STD value within 0.17 µm, an expanded uncertainty of measurement was within 5 µm, the angle error variation of the object’s rotational plane was within 0.031 degrees and nonlinearity was recorded within 0.006 per cent in a full scale. The proposed approach reduced the effect of the nonlinearity presented in the sensor. Thus, the accuracy and speed of the sensor were greatly increased. The specifications of the optimized sensor meet the requirements for high-accuracy devices and allow wide range of industrial application.

In this paper, COA-based BPNN is proposed for laser triangulation displacement sensor optimization, on the basis of the mathematical model, clarifying the working space and working angle on the measurement system.

Built upon three components (attitudes, subjective norms, and perceived behavioral control) of the theory of planned behavior (TPB), the purpose of this paper is to analyze the factors that influenced accounting students’ intention to pursue public accounting instead of private accounting as their career choice in China.

The TPB is used to predict the rational intention of accounting students in this study. A binary logistic regression analysis was applied to test all hypotheses because of its suitability.

The authors find that the variety and marketability of public accounting experiences, high turnover plus, low firm cohesion in the workplace, and perceived difficulties in traveling extensively affected students’ intentions to pursue the public accounting profession significantly. By highlighting these factors that affect students’ intention to pursue public accounting, this paper has important implications for the accounting educators and other stakeholders in China and other emerging economies.

By understanding the factors influencing the accounting students’ interests in pursuing public accounting, accounting educators and accounting firms could make some changes, redesign accounting curriculum, and enhance internship experience and recruiting process in order to increase more interests in public accounting. Professional organizations and policy makers might learn some lessons to take some actions to encourage young accounting professionals to work for public accounting firms. Moreover, this study has provided a valuable perspective to accounting educators, practitioners, and policy makers in other emerging economies with the same shortage of qualified public accountants.

The purpose of this paper is to integrate the Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM) and Palka et al.'s model to predict young Chinese consumers' mobile viral attitudes, intents and behavior.

A paper survey was administered to 835 college students in Beijing, Shanghai, Kunming, and Liuzhou in summer and fall, 2010. The data were subject to statistic analyses including Pearson correlation, structural equation modeling, and backward regression with SPSS and AMOS.

The SEM model testing results confirmed the chain of young Chinese consumers' viral attitudes to intents to actual behavior. Subjective norm, perceived cost and pleasure were significant predictors of their viral attitudes. Their viral attitudes, perceived utility and subjective norm predicted their intent to pass along entertaining electronic messages. Their intent to forward useful electronic messages was determined by their viral attitudes, perceived utility and market mavenism. Their viral attitudes, intents and market mavenism predicted their mobile viral behavior.

It pays to foster Chinese consumers' favorable attitudes toward mobile viral marketing. It is advisable to know both target consumers and their associates very well. It is recommended to convince Chinese consumers that their friends and relatives can benefit greatly from viral content forwarding. Mobile messages with entertaining, useful, relevant and self‐involved values can go viral more easily.

The paper is probably the first study the integration of the TPB, TAM and Palka et al.'s model to predict Chinese consumers' mobile viral attitudes, intents and behavior.

This paper aims to provide a new method to design a fuel efficient control strategy such as J₂ perturbation for deploying a constellation into a specified configuration. The nonspherical perturbation, mainly J₂ perturbation, is the dominant perturbation for low-Earth-orbit (LEO) satellites of a constellation. This perturbation can be utilized in the control strategy to lower fuel consumption enormously.

The relationship of the coupled variables, the relative right ascension of ascending node (RAAN) and the relative phase (RP), are analyzed. First-order approximation expressions of the relative RAAN (RRAAN) and the relative phase (RP) with respect to the semimajor axis are derived. According to the Gauss’ variational equations, the reduced explicit functions of these variables in regard to each active control are established. Based on these functions, control strategy design methods, including the preliminary planning and iterative corrections, are proposed. The numerical simulation is carried out to verify the proposed method.

The results indicate that the constellation can be deployed accurately about the semimajor axis, the RRAAN and the relative phase (RP) by the developed fuel efficient control strategy.

The proposed control strategy is limited for the orbital altitude where the J₂ perturbation is dominant.

The proposed effective method is applicable for the engineers planning an orbital control strategy of deploying satellites of a constellation.

The new control strategy can realize utilization of J₂ perturbation and an accurate deployment, simultaneously. Further, this paper provides practical help for satellite engineers.

The purpose of this paper is to establish a model to analyze the impacts of economic policy on the demand for electricity in China, including the impacts of fiscal and monetary policies.

With the development of electric reform, the impacts of economic policy on demand for electricity will be more and more obvious. It is difficult to analyze the impacts by a conventional model. CGE model is based on the theory of general equilibrium which is put forward by Walras, it describes the supplying and demanding relationship between the sectors of the economic system, a CGE model can recognize that an exogenous change (in policy or from other source) that affects any one part of the economy can produce repercussions throughout the system, it can also analyze the impacts of economic policy on electric power sector.

A CGE model and a social accounting matrix are established.

Accessibility and availability of data are the main limitations which model will be applied.

A very useful model to study the impacts of economic policy on electric power sector.

The new method to analyze the impacts of economic policy on electric power sector in China. The paper aims at policy makers and the researchers who deal with electric power demand and supply.

Measuring the diffusion of protests, or more generally, the diffusion of events, is an ongoing task in social sciences. This paper proposes an inter-event approach to study what types of protests tend to diffuse or decline. We develop a standardized, five-step procedure to measure what we define as “event diffusion momentum” (EDM): (1) employ event-based data containing information on the time, location, and features of each protest; (2) define the temporal and spatial ranges of interest; (3) for each observation, count the number of events before and after it within the defined ranges; (4) predict the numbers of post-event and pre-event protests with appropriate count models; (5) calculate the ratios of predicted values for each predictor and confidence intervals using the delta method. The ratio is the EDM. Applying this method to Dynamics of Collective Action (DoCA) data, we identify several micro- and macro-level factors associated with protest diffusion in the United States, 1960–1995. We conclude with the implications and generalizability of the proposed method.