Ioana Bradea

Grey incidence between KPIs and hospital performance

Purpose – Performance indicates how well the activities, operations and business processes of an enterprise are performed. In health care, performance illustrates the quality of medical services and targets the strategic objectives, the efficiency and effectiveness and the obtaining of the desired financial results. In economic analysis, the key performance indicators (KPIs) offers real, relevant and accurate information regarding the performance, using analysis and diagnosis techniques. The purpose of this paper is to discuss grey systems theory in order to bridge the KPIs and the hospital’s performance. Design/methodology/approach – Using the grey systems theory, the impact of seven selected KPIs (the beds utilization rate, the average length of hospitalization, the average cost of hospitalization/day, the proportion of physicians in total staff, the nosocomial infection rate, the death rate and the diagnostic concordance) on the hospital’s turnover is determined. Findings – By analyzing the grey incide...

A Healthcare Companies’ Performance View through OSN

In the new economic context, the on-line social networks (OSN) are gathering among their users a whole array of persons, with a diversified background, culture, opinions and needs. Here is the meeting point for persons looking for information on different domains and areas of interest and also here is the exchange land for thoughts, experiences, news, etc. As the companies have sensed the global phenomenon of the OSN, they have paid more attention to the on-line social environment, investing more in the social media campaigns. But what about the companies in the healthcare system? Are their customers seeking for information in OSN? And if so, to what extent the information provided here is useful? Namely, is the OSN affecting their performance?

Banking sector risks identification via GRA

The present paper gives a new perspective on the banking risks and on their influences on the banking sector as a whole. Due to the actual financial crisis, the banks are facing more and more complex risks, with difficult to measure and manage impacts. Among these risks, the one coming from their inside structure were depicted and analyzed in the paper. The main aim of the research is to find whether there is a strong relation between the identified categories of risks and banks evolution and in an affirmative case to see if this relation depends also on the banking sector. For this, a powerful grey theory tool was used, namely the GRA (grey relational analysis). Also, a case study was considered for a number of 16 banks spread in 4 groups based on the banking sector they belong to. The results were concluding as it can be seen.

Adjusting the errors of the GM(1, 2) grey model in the financial data series using an adaptive fuzzy controller

Purpose The purpose of this paper is to focus on the adjustment of the GM(1, 2) errors for financial data series that measures changes in the public sector financial indicators, taking into account that the errors in grey models remain a key problem in reconstructing the original data series. Design/methodology/approach Adjusting the errors in grey models must follow some rules that most often cannot be determined based on the chaotic trends they register in reconstructing data series. In order to ensure the adjustment of these errors, for improving the robustness of GM(1, 2), was constructed an adaptive fuzzy controller which is based on two input variables and one output variable. The input variables in the adaptive fuzzy controller are: the absolute error ei0(k)[%] of GM(1, 2), and the distance between two values xi0(k)[%], while the output variable is the error adjustment Aei0(k)[%] determined with the help of the above-mentioned input variables. Findings The adaptive fuzzy controller has the advantage that sets the values for error adjustments by the intensity (size) of the errors, in this way being possible to determine the value adjustments for each element of the reconstructed financial data series. Originality/value To ensure a robust process of planning the financial resources, the available financial data are used for long periods of time, in order to notice the trend of the financial indicators that need to be planned. In this context, the financial data series could be reconstituted using grey models that are based on sequences of financial data that best describe the status of the analyzed indicators and the status of the relevant factors of influence. In this context, the present study proposes the construction of a fuzzy adaptive controller that with the help of the output variable will ensure the error’s adjustment in the reconstituted data series with GM(1, 2).

How Impressionable Are You? - Grey Knowledge, Groups and Strategies in OSN

Today’s leading businesses have understood the role of “social” into their everyday activity. Online social networks (OSN) and social media have melt and become an essential part of every firm’s concerns. Brand advocates are the new leading triggers for company’s success in online social networks and are responsible for the long term engagement between a firm and its customers. But what can it be said about this impressive crowd of customers that are gravitating around a certain brand advocacy or a certain community? Are they as responsive to a certain message as one might think? Are they really impressed by the advertising campaigns? Are they equally reacting to a certain comment or news? How they process the everyday grey knowledge that is circulating in OSN? In fact, how impressionable they are and which are the best ways a company can get to them?

Grey Incidence between Banks' Risks and Their Performance

The present paper tries to give a new perspective on the banking risks and their influence on the profitability of the banking sector as a whole, with a tremendous impact on banks survival in now-a-days economy. Due to the more and more uncertain economical environment, this impact is even harder to be measured and managed. That is why here it can be identified a highly stringent need for some methods which are best working in uncertain conditions and what could work better than grey systems theory methods? Although it is quite new, grey system theory was able to impose quickly. In practice it has been successfully applied in the analysis, modeling, prediction, control and decision making in all areas. Its advantage is that it manages to achieve a good performance in tests conducted on a small number of data. The analysis is conducted through a country rating perspective.

Opinion influence in online social media environments — U grey system theory and agent-based modeling approach

The present paper aims to simulate an online environment in which both agents and consumers meet and exchange information related to certain types of goods (regular soft or durable goods, luxury soft of durable goods) on the purpose of establishing the number of agents a company need to “place” in the online environment in order to influence or change a persons opinion. On this purpose, a series of variables are defined using grey numbers and determined using a questionnaire and face-to-face interviews to sales managers. Based on them, an agent-based model is proposed.

Grey sentiment analysis using SentiWordNet

Sentiment analysis is one of the most important topics in the Natural Language Processing field, aiming to determine whether a text expresses a positive, negative or neutral perception. In most sentiment analysis applications, a central role is played by the sentiment lexicons, which are lexical resources that include lists of tokens, together with the associated polarity score for each token or term. However, such approaches do not take into consideration the fact that a term might have distinct and sometimes even opposite sentiment polarities in different contexts. The present paper uses the grey system theory in order to associate terms with the most likely intervals of polarity, in order to enable a more accurate sentiment understanding, through grey sentiment analysis, even in limited information contexts, such as social media analysis.

Healthcare Risk Management Analysis - A Bibliometric Approach

Using a large-scale dataset from WoS, this paper explores the publications on healthcare risk management, through bibliometric analysis. The bibliometric analysis reflects how research in hospital risk management and healthcare management evolved over time, offering insights on the most relevant and influential research. Based on the idea that researchers publish their most important results in articles, conferences, books and reviews, there is diffusion in this research field, with many reference countries. The bibliometric analysis reflects the growing interest of research for the area of healthcare risk management. The need to provide high quality medical services requires the design and implementation of a set of key performance indicators for each strategic objective set by the hospital management.