Improvements for determining the number of clusters in k-means for innovation databases in SMEs

The risk of adverse events in a hospital evaluation is an important process in healthcare management. It involves several technical, social, and economical aspects. The purpose of this paper is to propose an integrated approach to evaluate the risk of adverse events in the hospital sector.,This paper aims to provide a decision-making framework to evaluate hospital service. Three well-known methods are applied. More specifically are proposed the following methods: analytic hierarchy process (AHP), a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology developed by Thomas L. Saaty in the 1970s; decision-making trial and evaluation laboratory (DEMATEL) to construct interrelations between criteria/factors and VIKOR method, a commonly used multiple-criteria decision analysis technique for determining a compromise solution and improving the quality of decision making.,The example provided has demonstrated that the proposed approach is an effective and useful tool to assess the risk of adverse events in the hospital sector. The results could help the hospital identify its high performance level and take appropriate measures in advance to prevent adverse events. The authors can conclude that the promising results obtained in applying the AHP–DEMATEL–VIKOR method suggest that the hybrid method can be used to create decision aids that it simplifies the shared decision-making process.,This paper presents a novel approach based on the integration of AHP, DEMATEL and VIKOR methods. The final aim is to propose a robust methodology to overcome disadvantages associated with each method.

An integrated approach to evaluate the risk of adverse events in hospital sector: From theory to practice

The past few decades showed inadequate discussion of the impact of employees’ knowledge sharing and its diffusion on advancing banks’ long-term sustainability. The objective of the study is to examine the role of employees’ knowledge sharing on the sustainable performance of the banks operating in Bangladesh. Furthermore, this study tested the “moderated mediation model” of knowledge hiding and employees’ ambidexterity on the association above. The researchers applied the deductive reasoning method through the application of quantitative techniques, using structural equation modeling. Finally, 287 respondents from different banks were chosen through a self-administered questionnaire survey in the capital city of Dhaka. The findings indicated that all the predictor variables significantly explain the outcome variable, except the influence of knowledge sharing. Mediation analysis showed that employees’ ambidexterity mediated the association between knowledge sharing and sustainable performance. Surprisingly, moderation analysis revealed that the influence of knowledge sharing on employees’ ambidexterity is not affected by knowledge hiding. This study adds to the existing literature by demonstrating the importance of knowledge hiding, along with explaining how knowledge sharing can motivate and influence employees to achieve sustainable performances. In addition, the main contribution of this study is to advance knowledge and add values in the forms of knowledge creation, preservation, and dissemination among practitioners, banking professionals, and academics for utilizing their domain-specific areas to increase long-term sustainability.

https://www.mdpi.com/2071-1050/12/3/908/pdf

The Influence of Knowledge Sharing on Sustainable Performance: A Moderated Mediation Study

Every day organizations pay more attention to Human Resources Management, because this human factor is preponderant in the results of it. An important policy is the Performance Evaluation (ED), since it allows the control and monitoring of management indicators, both individual and by process. To analyze the results, decision making in many organizations is done in a subjective manner and in consequence it brings serious problems to them. Taking into account this problem, it is decided to design and apply diffuse mathematical procedures and tools to reduce subjectivity and uncertainty in decision-making, creating work algorithms for this policy, which includes multifactorial weights and analysis with measurement indicators that they allow tangible and reliable results. Statistical techniques (ANOVA) are also used to establish relationships between work groups and learn about best practices.

/pdf/fuzzy-logic-applied-to-the-performance-evaluation-honduran-48x6ne4xqu.pdf

Fuzzy Logic Applied to the Performance Evaluation. Honduran Coffee Sector Case

The occurrence of faults in distribution systems has a negative impact on society, and their effects can be reduced by fast and accurate diagnostic systems that allow to identify, locate, and correct the failures. Since the 1990s, fuzzy logic and other artificial intelligence techniques have been implemented to identify faults in distribution systems. The main objective of this paper is to perform fault diagnoses based on fuzzy logic. For conducting the study, the IEEE 34-Node Radial Test Feeder is used. The data was obtained from ATPDraw-based fault simulation on different nodes of the circuit considering three different fault resistance values of 0, 5, and 10 ohms. The fuzzy rules to identify the type of fault are defined using the magnitudes of the phase and neutral currents. All measurements are taken at the substation, and the results show that the proposed technique can perfectly identify and locate the type of failure.

/pdf/fault-diagnosis-on-electrical-distribution-systems-based-on-9hxa3lwawn.pdf

Fault Diagnosis on Electrical Distribution Systems Based on Fuzzy Logic

The present article shows the results of an investigation carried out on the use of alternatives to carry out work accident studies in an objective manner in three production sectors that are of high risk: the electric power production sector, cement production and oil refining sector, so the main objective is focused on identifying the influential variables and the regression model that best explains the accident in each of these sectors and perform a comparative analysis between them. Among the techniques and tools used (data mining) are those related to multivariate statistics and generalized linear models and through the Akaike information criterion and Bayeciano criterion, it was possible to determine that the best regression model that explains the accident rate in two of the sectors studied is the negative binomial (cement and petroleum refining), while in the electric power sector, the best fit model resulted in Logistic Regression. In turn, for the three sectors in general, the variables that have the most significant impact are related to aspects such as: management commitment, occupational safety climate, safety training, psychosocial aspects and ergonomic sources, this result was corroborated by means of an accident analysis carried out in these three sectors.

/pdf/models-of-multivariate-regression-for-labor-accidents-in-hr1jrmaoip.pdf

Models of Multivariate Regression for Labor Accidents in Different Production Sectors: Comparative Study

The investigation responded to the need outlined by directive and interested parts, in relation to the lack of mechanisms for the administration control and the need to reduce the amount of data when making measurements of performance in the cement industry. Throughout the employment of an outlined methodology, it was obtained an Integral Index of Acting that relates to the aspects that controlled the acting of the processes in function of managerial strategies, of easy mensuration as a result, automatic and that it facilitates to summarize a big amount of criteria and data, through their standardization, and thus the realization of comparisons with other production plants.

/pdf/methodology-for-the-reduction-and-integration-of-data-in-the-zjrq1dv7p0.pdf

Noel Varela Izquierdo

Papers

Fuzzy Logic Applied to the Performance Evaluation. Honduran Coffee Sector Case

Models of Multivariate Regression for Labor Accidents in Different Production Sectors: Comparative Study

Methodology for the Reduction and Integration of Data in the Performance Measurement of Industries Cement Plants

Methodology of Application of Diffuse Mathematics to Performance Evaluation

Selection of the best regression model to explain the variables that influence labor accident electrical company case