PurposeIn the age of a knowledge-based economy and following extensive socio-economic changes, the success of organizations is not limited to gaining financial and material resources. Instead, it depends on the acquisition of intangible assets that can be used to achieve a sustainable competitive advantage. In the new strategic environment, organizations will thrive when they see themselves as a learning organization whose goal is to improve intellectual capital continually; an organization that cannot increase its intellectual capital cannot survive. The term intellectual capital is used in the overlap of all assets, intangible resources and non-physical resources of an organization, including processes, innovation capacity and implicit and explicit knowledge of its members and partner network. However, despite the growing importance of intellectual capital and cloud computing as vital resources for organizations' competitive advantage, there is a limited understanding of them. Simultaneously, the management of intellectual capital enables organizational managers to create, nurture, control and preserves a strong competitive advantage source, the advantage that competitors will not easily capture. So, the main objective of the present investigation is to check out the factors affecting the adoption of intellectual capital management systems based on cloud computing in hospitals.Design/methodology/approachIn the last two decades, we have moved toward economics, where investment in Information Technology (IT), human resources, development, research and advertising is essential to maintain competitive advantage and certify the sustainability of organizations. Therefore, it can be stated that the economic value is the creation and management of intangible assets, which are referred to as intellectual capital. On the other hand, cloud computing is presented as a new paradigm for hosting and providing services through the Internet. Cloud computing can lead to too many benefits to organizations, including cost reduction, flexibility and improved performance. The present article examines how optimal intellectual capital management can be achieved using cloud computing. So, seven hypotheses were developed through the dimensions of technology, environment, organization and innovation. In this study, the path analysis was performed using Analytic Hierarchy Process (AHP) and Partial Least Squares (PLS). By reviewing the literature related to the model of technology, organization, environment and innovation dissemination theory, four main criteria, and 15 sub-criteria were identified based on the opinions of specialists, professors and IT experts based on AHP and PLS methods.FindingsThe results of this investigation confirmed all the hypotheses. The results illustrated that environmental and technological factors should be regarded more when adopting intellectual capital management systems based on cloud computing. The results also indicated that intellectual capital highly influences improving performance. Furthermore, cloud apps, like other disruptive technology, deliver superior benefits while still presenting a slew of realistic challenges that must be tackled. In order to draw a growing customer base to this business model, software vendors should resolve these concerns. The literature revealed that the computing industry is making tremendous strides around the world. Nevertheless, in order to achieve a faster and softer adoption, newer and more advanced techniques are still required.Research limitations/implicationsThe research outcomes can significantly impact a wide range of organizations, such as health-related organizations. However, there are some limitations; for example, the sample is limited to one country. Therefore, future studies can measure the data of this study in different samples in different countries. Future researchers can also boost the model's predictive capability to adopt cloud computing in other organizations by adding environmental, organizational, innovation and other technical factors.Practical implicationsManagers will use these emerging innovations to minimize costs and maximize profits in the intellectual capital management competition. An effective cloud computing based on an electronic human resource management system can significantly increase system performance in industries. The investigators expect that the results will direct clinicians and scholars into a more advanced and developed age of cloud-based apps.Originality/valueInvestigations on the impact of cloud computing on intellectual capital management are rare. Accordingly, this investigation provided a new experience in terms of intellectual capital in the field of cloud computing. This study filled the scientific research gap to understand the factors affecting intellectual capital management systems based on cloud computing. This study provides a better insight into the power of organizational and environmental structure to adopt this technology in hospitals.
As an important part of the development of green economy, the green investment evaluation system provides a method to identify the performance of the investment environment and also guides the design of green investment plans. This article is aimed at analyzing the application of cloud computing and information fusion technology in the green investment evaluation system, using empirical analysis, qualitative and quantitative analysis, data integration, and distributed computing algorithms to carry out research. Data acquisition is mainly through cloud platform information fusion, to evaluate the investment subject, investment object, and investment vehicle of green investment. Qualitative and quantitative analysis is mainly through the definition of prerequisites by stipulating certain aspects of green, and the analysis of the country’s data changes in a certain time zone. Focus on the qualitative analysis and research on the green benefit attributes of a certain thing. In addition, by analyzing the influencing factors of the investment development status of green industries in different countries, such as green products, green projects, and green funds, it proves that the application of cloud computing and information fusion technology has a huge effect on the green investment evaluation system. Experimental data shows that in the past five years, investment in fixed assets in my country’s major industries accounted for the proportion of fixed asset investment in the whole society, and investment in environmental protection and energy supply industries has continued to rise. This upward trend is manifested in the fact that the amount of energy investment is increasing year by year. The development trend is the strongest during the development period and the entry period, and its data grows the most rapidly, while investment in the transportation industry has always been listed in the tables. For the first place in the industry, the highest was 20.84%.
Clustering fusion is a large combination of different algorithms or the same algorithm using different parameters the members of quantitative clustering are fused by fusion function, and the final clustering results are obtained. Clustering fusion has become a research hotspot in the field of data mining. However, the traditional clustering fusion method the method usually involves all the cluster members produced. But in supervised classification learning, Great progress has been made in the selection of classification fusion, and the selectivity for unsupervised classification has been improved. Clustering fusion has been paid more and more attention only in recent years. The study shows that the selective clustering fusion the combined method can improve the accuracy of clustering analysis. This paper aims at selective polymerization. Data dimensionality reduction, selection strategy, fusion function design and other algorithms in class fusion are studied. The selective clustering fusion algorithm is applied to the analysis of multiple clustering problems.
With the development of economy and technology, data mining which is based on databases and business intelligence has been developed and widely applied to all fields, financial field included. It can explore hidden, useful information to help decision makers to search for the relationship among data and find out what has been ignored. Compared with traditional financial analysis, data mining can deal with massive financial data, to help the company's investors and policy makers to have in-depth understanding of the company's financial situation, and make right decisions. Here we design a financial data analysis system based on data mining model, and we conduct a comparative test by Logistic regression algorithm and decision tree algorithm, and the results show that using data mining algorithms to predict ROE business is feasible.
the management of intangible assets is becoming more and more important in enterprise management, however,there exist many problems in management of intangible assets in our country at present and the traditional management models are no longer suitable for the management of intangible assets in the new period that there appears an urgent call for the innovation of intangible assets management models. Based on the author's years of practical experience, this paper first analyzes current problems existing in the management of intangible assets in enterprises, and then establishes innovation system of intangible assets in enterprises from contents, organization, tools and system.
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