Variational Embedding Multiscale Sample Entropy: A Tool for Complexity Analysis of Multichannel Systems

Entropy-based methods have received considerable attention in the quantification of structural complexity of real-world systems. Among numerous empirical entropy algorithms, conditional entropy-based methods such as sample entropy, which are associated with amplitude distance calculation, are quite intuitive to interpret but require excessive data lengths for meaningful evaluation at large scales. To address this issue, we propose the variational embedding multiscale sample entropy (veMSE) method and conclusively demonstrate its ability to operate robustly, even with several times shorter data than the existing conditional entropy-based methods. The analysis reveals that veMSE also exhibits other desirable properties, such as the robustness to the variation in embedding dimension and noise resilience. For rigor, unlike the existing multivariate methods, the proposed veMSE assigns a different embedding dimension to every data channel, which makes its operation independent of channel permutation. The veMSE is tested on both stimulated and real world signals, and its performance is evaluated against the existing multivariate multiscale sample entropy methods. The proposed veMSE is also shown to exhibit computational advantages over the existing amplitude distance-based entropy methods.

Effect of Collaborative Governance on Medical and Nursing Service Combination: An Evaluation Based on Delphi and Entropy Method

[Background]: Improvement of synergies in medical and nursing services can help governments to optimize the allocation of medical resources; however, an appropriate evaluation method is critical for a suitable decision process in this regard. [Method]: To assess the medical and nursing service combination (MNSC) at a regional level, this study applied a five-dimension evaluation index composed of 28 basic response areas related to the MNSC development status in China, determining its respective weight through the Delphi and entropy methods. [Result]: This empirical exercise analyzed the MNSC supply system by interviewing nine heads of medical and nursing institutions and eleven healthcare-related government personnel during August of 2020 in Xinxiang City, Henan province, P.R China. Results showed: (1) public satisfaction with the fees charged by Medical and Nursing service Institutions (MNSI); (2) Medicare and supply services’ policy publicity; (3) the external financing situation of MNSI; (4) the medical staff’s professional quality; (5) the medical facilities and supply of MNSI; and (6) that the recognition level of the development plan of MNSI scored the highest effect on the synergy of MNSC supply among the assessed factors. [Conclusion]: These results showed that an evaluation based on the Delphi and entropy methods can effectively integrate the opinions of experts and related institutions to evaluate synergies on the medical and nursing service supply.

The Influence of E-Marketing on Performance of Real Estate Enterprises: Based on Super-Efficiency DEA and Grey Entropy Methods

E-marketing is an important tool for real estate enterprises. We evaluate 3 online marketing channels of 44 Chinese real estate companies. Super-efficiency DEA and grey entropy methods are applied to analyse the influence of E-marketing on the performance of real estate enterprises. We find that E-marketing will affect the business performance of real estate companies. Real estate company managers should adopt more strategies to improve corporate performance.

Assessing the level of digital maturity of enterprises in the Central and Eastern European countries using the MCDM and Shannon’s entropy methods

The process of global economic digitalization is a natural stage of evolutionary changes resulting from a dynamic development of information and communication technologies. Having appreciated the importance and advantages of digital transformation, individual countries began to strive to introduce it as soon as possible. In this context, it is important to study the level of digital maturity in Central and Eastern Europe, where the level of digitization is relatively low. This article assesses the level of digital readiness of enterprises in these countries based on 14 determinants characterizing the most important areas of the digitalization process. The research was carried out for 11 countries from the region, both for all and manufacturing enterprises. Multi-criteria analysis aimed at assessing the digital maturity of countries were performed using the Multi-Criteria Decision-Making methods (the TOPSIS, MOORA, VIKOR), and entropy methods for delineating the weights of the determinants. In order to obtain an unambiguous assessment of the determined digital maturity, the mean-rank method was applied. The method of multidimensional scaling allowed for the analysis of similarities between the countries in question. The results showed that the level of digital maturity in the Central and Eastern Europe countries varies greatly and is lower than in other European Union countries.