Investigation and analysis of the effectiveness and influencing factors of internal control in Chinese enterprise based on wireless network
The internal control system of the enterprise is an important application method to improve the operational efficiency of enterprises and reduce unnecessary cost expenditures, and there are many factors that affect its effectiveness. How to find out the key factors in many influencing factors and adopt positive improvement measures to improve the internal control system and to improve its effectiveness has become a new topic for Chinese experts and scholars. Chinese enterprises are selected as the research object, and in-depth analysis of the influencing factors of the effectiveness of the internal control of the company through questionnaire surveys and in-depth discussions on the internal control of the enterprise by making full use of the real data of corporate internal control are conducted; at the same time, the optimal strategy is put forward to the optimization of the distributed database query process in the process of research, so as to provide scientific basis for the enterprise to build a scientific and perfect internal control system.
KeywordsSQL database Enterprise Internal control
The Committee of Sponsoring Organizations of the Treadway Commission
Disk operate system
Enterprise Rights Management
Not Only SQL
Securities and Exchange Commission
Sensor protocol for information via negotiation
Torrify Ethical Software License Agreement
With the rapid development of economy, the competitive environment of enterprises is becoming more intense, the development background is getting more complicated, and the corresponding risk factors are also increasing . Enterprises need to avoid the risks existing in the market as far as possible to gain a foothold in a fast-growing society and achieve better economic benefits; for this, the business-related internal controls need to be done well. The effectiveness of internal control of an enterprise is not isolated in the development process of the enterprise, but is linked to the specific control objectives of the enterprise and related control processes . If the internal control of an enterprise wants to be effective, the specific process of control needs to provide a reasonable and scientific guarantee for the control objective to be achieved. However, because the internal control is subject to certain restrictions in the implementation process, the guarantee is not absolute . When the internal control is implemented by the enterprise, it will be influenced by many factors, such as the inaccurate operation of the control process and the dramatic changes in the environment of the enterprise . Therefore, a series of specific factors need to be paid more attention in the control process to ensure the effectiveness of internal control . The effectiveness of internal control mainly covers the specific design aspects and the effectiveness of the control process . If the internal control is supposed to run smoothly and ultimately achieve specific control objectives, in terms of the corresponding design, it will be scientific, reasonable, and standard, so as to control the target eventually to provide a solid foundation and effective guarantee. In the specific process of internal control, it is necessary to ensure that the internal control is effective in accordance with the internal control in order to ensure the effectiveness of internal control .
1.1 State of the art
In 1992, the COSO committee released the internal control—integration framework (revised in 1994) to define internal controls as follows: It is a process that is influenced by the company’s board of directors, management, and other staff. It aims to provide a reasonable guarantee of business effectiveness and efficiency, reliability of financial reports, and compliance with appropriate regulations . In 2004, the COSO Committee released the Enterprise Risk Management—Integration Framework (referred to as the ERM Framework) to shift the focus of corporate internal control to risk management . At present, the empirical research on the effectiveness of internal control is limited . At abroad, after the Sarbanes Oxley Act was enacted, American scholars began to focus on the financial report of the effectiveness of internal control: an empirical study. They disclose the substantive loopholes of internal control according to the requirements of SEC and of enterprises, as the criteria for evaluating the effectiveness of internal control of financial reports. At home, only some scholars have carried out relevant researches. It is believed that the effectiveness of internal control cannot be evaluated in general. It should be measured from the four objectives, compliance objectives, reporting objectives, operating objectives and strategic objectives. Based on the regulations of SEC, the internal control of compliance target, internal control of reporting target, internal control of management target, and internal control of strategic target are put forward from the objective of internal control.
2.1 Distributed database data allocation algorithm
According to the generation of chromosome clusters, the use of random numbers in the traditional mode has certain limitations and blindness. In this paper, the average distribution method is used to cover the initial population as much as possible to improve the probability of finding the optimal solution. The strategy of chromosome selection is improved, and the optimal selection algorithm is added. The traditional genetic algorithm is based on roulette, which may cause some loss of excellent chromosomes, and the optimal selection algorithm is added to solve this problem. Dynamically changing the probability of crossover and mutation ensures the generation speed of new chromosomes, ensures the diversity of chromosomes, and ensures excellent chromosomes are not destroyed; algorithm is not easy to fall into local optimum. The determination of dynamic probability is related to changes in fitness. The definition of the chromosome definition and fitness function of the genetic algorithm is elaborated below.
2.2 Wireless sensor network broadcast authentication
μ TESLA protocol greatly reduces the computational strength of broadcast authentication and improves the speed of broadcast authentication. But its disadvantage is that it requires the node to store the message before the authentication key is published, causing storage problems and easily causing DoS attacks; during the initialization of the protocol, the base station sends the protocol initial information to the sensor node in a single broadcast mode. In addition, long network life cycles require long key chains. In order to reduce the cost of the key chain length and the initial information of the distribution protocol, Liu et al. proposed the layered μTESLA protocol. When layering μTESLA, the network life cycle is first divided into high-level time intervals, and then each high-level time interval is divided into low-level time intervals. Each interval generates a key chain of a corresponding length. The higher level key chain authenticates the initial information of the lower level key chain; the lower level key chain authenticates the broadcast data packet.
3 Result analysis and discussion
It can be seen from the figure above that the optimized distributed database query method based on genetic algorithm is superior to the general distributed database query and requires less time. In the aspect of data query, traditional centralized database is based on SQL language for data query operation, but in distributed database, the query operation needs to consider several factors; the performance of query algorithms varies greatly between different scenarios. The data query optimization algorithm is based on genetic algorithm which is proposed and researched in this paper. Considering the related factors, the optimal solution is larger. Practical application shows that based on the optimization algorithm, the query time of distributed database can be reduced significantly.
In order to test the correctness and efficiency of adaptive and mutation operators, it is necessary to compare the performance of the algorithm under different crossover and mutation probabilities. Comparing the above probabilistic coefficients through experiments, and using the method of sorting and selecting operators, the following results are obtained by assigning different values of the probability coefficients a and b: the result of taking different values of probability coefficients. It is found by figure that when a = 0.9, evolution is faster, but it will soon enter precocity and fall into local optimum; when a = 0.7, evolution is too slow to achieve efficient search; when b = 0.2, there is less variation and easy to fall into the local area; and when b = 0.4, there are too many mutations that prevent many excellent chromosomes from being effectively preserved, but they are eliminated, which affects the speed of evolution. Only when a = 0.8 and b = 0.3, evolution has a high speed, and it is not easy to enter “precocity” and search for high efficiency and stability. Among them, fmax is the maximum value of the population fitness function, and fmin is the minimum value of the population fitness function, f is the fitness function value of adjacent individuals after individual fitness values are sorted, and k is the number of individuals in the population. When the fitness tends to be consistent, we can achieve the effect of “genetic catastrophe” through the change of b.
Prediction error of different models
Linear regression model
Maximum relative error absolute value Emac/%
Average relative error Eave/%
Root mean square error RMSE (104)
BL has made great contributions to the direction of the internal control survey of Chinese enterprises in wireless network. PW has done a lot of work on the effectiveness and influencing factors of internal control in Chinese enterprises and has paid a lot of efforts. Both authors read and approved the final manuscript.
Bo Liu, Doctor of Management, Associate professor. Graduated from Sichuan University in 2011. Worked in Anhui University of Finance and Economics. His research interests include Audit and Internal Control.
Pingshui Wang, Doctor of Engineering, professor. Graduated from Nanjing University of Aeronautics and Astronautics in 2013. Worked in Anhui University of Finance and Economics. His research interests include information technology and information security.
The authors declare that they have no competing interests.
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