The E-Commerce Investment and Enterprise Performance Based on Customer Relationship Management

In the current dynamic and complex competitive environment, the implementation of enterprise e-commerce plays an important role in the development of external business process activities. Through the Internet, information sharing and business process collaboration between enterprises and customers can be realized. This kind of e-service activity based on e-commerce process is particularly important for customers. However, many business managers have some doubts about the implementation of customer service-oriented online business activities, because customer service-oriented online business activities need a lot of IT investment, and the performance of this e-business activities is not easy to measure.

The E-Commerce Investment and Enterprise Performance Based on Customer Relationship Management

In the current dynamic and complex competitive environment, the implementation of enterprise e-commerce plays an important role in the development of external business process activities. Through the Internet, information sharing and business process collaboration between enterprises and customers can be realized. This kind of e-service activity based on e-commerce process is particularly important for customers. However, many business managers have some doubts about the implementation of customer service-oriented online business activities, because customer service-oriented online business activities need a lot of IT investment, and the performance of this e-business activities is not easy to measure.

Relationship Model between Human Resource Management Activities and Performance Based on LMBP Algorithm

The research on the relationship between human resource management activities and performance is an important topic of enterprise human resource management research. There are some errors between the relationship between human resource management activities and performance and the real situation, so it is impossible to accurately predict the performance fluctuation. Therefore, the relationship model between human resource management activities and performance based on the LMBP algorithm is constructed. Using the Levenberg–Marquardt (LM) algorithm and BP (back-propagation) neural network algorithm to establish a new LMBP algorithm, control the convergence of the new algorithm, optimize the accuracy of the algorithm, and then apply the LMBP algorithm to predict the risk of performance fluctuation under human resource management activities of enterprises, the indicators of human resource management activities of enterprises are determined, to complete the mining of enterprise performance data, the grey correlation analysis is combined, and the relationship model between human resource management activities and performance is built. The experimental samples are selected from CSMAR database, and the simulation experiment is designed. Using different algorithms to forecast the fluctuation of enterprise performance, the experimental results show that the LMBP algorithm can more accurately reflect the relationship between enterprise HRM and performance.

Enterprise Performance Management following Big Data Analysis Technology under Multisource Information Fusion

With the development of the Internet, big data collection, analysis, and processing are flourishing. The study aims to explore the performance management of power enterprises based on multisource information fusion and big data. First, the application of big data to enterprise management is analyzed. Second, the multisource information fusion method is introduced, and the multisource information fusion model is implemented. Finally, the fuzzy language algorithm is used to evaluate the performance management of power enterprises. The results show that the proposed multisource information fusion algorithm has high efficiency in evaluating enterprise performance management. The evaluation result is closer to the actual value than other algorithms, and the maximum acceleration ratio can reach 7, indicating that the algorithm is suitable for processing big data. The performance evaluation shows that enterprises pay most attention to the quality of their products; the weight reached 0.414; and the index weight difference is large. This study promotes the reform of the performance management mode and improves the management efficiency of enterprises through the proposed enterprise performance management strategy. It provides a great reference for the application of big data and information fusion technology.

Customer relationship marketing & enterprise performance

The seeming eternal pursuit of profit by financial institutions and other enterprises have proved to be short-sighted judging from recent studies. Emphases have shifted to securing the goose that lays the golden-egg (the customer) rather than the egg itself. This study focused on the imperative of deploying evolving customer centric platforms such as CRM to manage customer needs satisfactorily to guarantee continued patronage and profit (performance). CRM is revealed as a competitive strategy hotly becoming popular among Nigerian banks - extant literatures on its dynamics were clinically x-rayed. Models of relationship management such as relational benefit, network and relational quality models were discussed in relation to service offerings. Survey research was used in a cross-sectional study to test the nature of association between CRM predictor variables of interactive marketing, service quality and bonding among leading banks in the South-South geopolitical zone of Nigeria. These variables were tested to ascertain whether they would become significant predictors of performance among the leading banks sampled. Outcome reveals a positive association and a strongly significant influence at 0.05%. This necessitated the rejection of all two hypotheses tested.

Engineering Financial Performance Evaluation of Wireless Network Based on Intelligent Neural Network Model

Under the global economy, enterprises in the financial industry are facing plenty of opportunities and severe challenges. Aimed at providing a reference enterprise performance evaluation system for related enterprises, the proposed model helps enterprises to learn and sort out their own performance evaluation system according to this structure. A prediction model of BP neural network (BPNN) based on the wireless network is studied as the performance data prediction algorithm. Firstly, the feasibility of this algorithm is analysed through prediction training. Secondly, the proposed neural network algorithm is compared with the traditional algorithm for data prediction. It turns out that this neural network prediction algorithm based on wireless communication is not only universal to the prediction data but also superior to the traditional prediction algorithm in both error gap and relative average error compared with other traditional algorithms. On this basis, the particle swarm optimization (PSO) algorithm is also used to evaluate the performance indicators of three enterprises, and accurate numerical values are obtained to express the corresponding results. Therefore, it is concluded that the subalgorithm can be applied to the enterprise performance evaluation team in the financial industry.