KNOWLEDGE STRATEGIES TOOLS FOR MANAGING ENTERPRISE CRISIS

The current economy is granting a widely interest to any activities involving knowledge. In the recent years, the number of the so-called knowledge-based organizations has reached a phenomenal rate of growth. Along with knowledge organizations, knowledge management started to play an important role in building the business strategy. Current paper identifies the knowledge gaps which threaten companies’ existence and underlines some knowledge tools based on competency-models to mitigate these gaps. Some statistical measurements for quantifying the strategic impact of using such intelligent tools are also described.knowledge, management, enterprises, crisis, competences

ESTABLISHING THE MOST INFLUENCING CAUSES OF COMPANIES’ FINANCIAL HEALTH AND PERFORMANCE – A GREY FUZZY APPROACH

The core of our paperwork consists in construction of a model for determining a hierarchy of qualitative and quantitative causes that are influencing service companies’ financial health. While the quantitative causes are objectively measurable, the qualitative causes are mainly subjectively measurable, quantified based on some experts’ opinion. In order to reduce the degree of subjectivity, we took advantage of methods offered by fuzzy systems, mainly in construction of the expertons. Expertons are in fact intervals built using the ϕ-fuzzy sub-set and the opinion of several experts over a certain problem. Furthermore, after constructing the expertons, we use the methods offered by grey systems theory and fuzzy sub-sets arithmetic to determine the degree of influence of each qualitative and quantitative cause on company’s performance. By classifying the causes and acting on the most important of them, the activity of the analyst can be really improved and the company’s performance will rise.service companies; fuzzy sets; grey systems theory; fuzzy sub-sets arithmetic; financial health

Business Ontology for Evaluating Corporate Social Responsibility

This paper presents a software solution that is developed to automatically classify companies by taking into account their level of social responsibility. The application is based on ontologies and on intelligent agents. In order to obtain the data needed to evaluate companies, we developed a web crawling module that analyzes the company’s website and the documents that are available online such as social responsibility report, mission statement, employment structure, etc. Based on a predefined CSR ontology, the web crawling module extracts the terms that are linked to corporate social responsibility. By taking into account the extracted qualitative data, an intelligent agent, previously trained on a set of companies, computes the qualitative values, which are then included in the classification model based on neural networks. The proposed ontology takes into consideration the guidelines proposed by the “ISO 26000 Standard for Social Responsibility”. Having this model, and being aware of the positive relationship between Corporate Social Responsibility and financial performance, an overall perspective on each company’s activity can be configured, this being useful not only to the company’s creditors, auditors, stockholders, but also to its consumers.corporate social responsibility, ISO 26000 Standard for Social Responsibility, ontology, web crawling, intelligent agent, corporate performance, POS tagging, opinion mining, sentiment analysis

Financial contagion and identifying speculative frenzies: Unraveling price bubbles in cryptocurrency markets

This research investigates the occurrence of financial bubbles in the cryptocurrency market and highlights the factors that may influence the formation of these bubbles. Three cryptocurrencies were analyzed: Bitcoin, Ethereum, and Cardano, and our findings showed that these cryptocurrencies exhibited potential bubbles during the three-year period under study, from 2020 to 2023. To detect financial bubbles, the Exponential Curve Fitting Model (EXCF) model was used. Events such as the Covid-19 pandemic and the Russia-Ukraine conflict were examined from the perspective of their potential impact on the cryptocurrency market and investor behavior. The study also illustrated how investors’ behavior, whether rational or influenced by external factors, as well as internal factors such as panic levels and knowledge in the financial-economic domain, were analyzed

Quality of Life and Psychological Distress among Patients with Small Renal Masses

Quality of life (QoL) and psychological distress represent an important aspect of the daily life of cancer patients. The aim of this systematic review was to critically analyze available literature regarding QoL and psychological distress in patients with small renal masses (SRMs). (2) Methods: A systematic search of EMBASE, PUBMED and American Psychological Association (APA-net) was performed on 30 April 2022. Studies were considered eligible if they included patients with SRMs, had a prospective or retrospective design, included at least 10 patients, were published in the last 20 years, and assessed the QoL or psychological distress in patients that underwent active surveillance (AS) in comparison to those that underwent ablation/surgery treatments. (3) Results: The patients that underwent AS were statistically significantly older, with smaller renal masses than those that underwent surgery/ablation. A study showed a significant reduction in total scores of Short Form-12 (SF-12) among AS patients when compared to partial nephrectomy (PN) patients at enrollment (95.0 ± 15.8 vs. 99.1 ± 13.9), 2 years (91.0 ± 16.4 vs. 100.3 ± 14.3), and at 3 years (92.9 ± 15.9 vs. 100.3 ± 14.3), p < 0.05, respectively. That was mainly due to lower physical health scores. On the other hand, another study showed that AS patients with a biopsy-proven malignant tumor had a worse psychological distress sub-score (PDSS) compared to patients treated with surgery/ablation after biopsy. (4) Conclusions: It seems that there is an influence on QoL and psychological distress while on AS of SMRs. However, due to the low amount of available data, the impact of AS or active treatment on QoL or psychological distress of patients with small renal masses warrants further investigation

New Wave of COVID-19 Vaccine Opinions in the Month the 3rd Booster Dose Arrived

Vaccination has been proposed as one of the most effective methods to combat the COVID-19 pandemic. Since the day the first vaccine, with an efficiency of more than 90%, was announced, the entire vaccination process and its possible consequences in large populations have generated a series of discussions on social media. Whereas the opinions triggered by the administration of the initial COVID-19 vaccine doses have been discussed in depth in the scientific literature, the approval of the so-called 3rd booster dose has only been analyzed in country-specific studies, primarily using questionnaires. In this context, the present paper conducts a stance analysis using a transformer-based deep learning model on a dataset containing 3,841,594 tweets in English collected between 12 July 2021 and 11 August 2021 (the month in which the 3rd dose arrived) and compares the opinions (in favor, neutral and against) with the ones extracted at the beginning of the vaccination process. In terms of COVID-19 vaccination hesitance, an analysis based on hashtags, n-grams and latent Dirichlet allocation is performed that highlights the main reasons behind the reluctance to vaccinate. The proposed approach can be useful in the context of the campaigns related to COVID-19 vaccination as it provides insights related to the public opinion and can be useful in creating communication messages to support the vaccination campaign

A Two-Door Airplane Boarding Approach When Using Apron Buses

Boarding is one of the major processes of airplane turnaround time, with a direct influence on the airline companies’ costs. From a sustainable point of view, a faster completion of the boarding process has impact not only on the airline company’s long-term performance, but also on customers’ satisfaction and on the airport’s possibility of offering more services without additional investments in new infrastructure. Considering the airplane boarding strategies literature, it can be observed that the latest papers are dealing with developing faster boarding strategies, most of them considering boarding using just one-door of the aircraft. Even though boarding on one-door might be feasible for the airports having the needed infrastructure and sufficient jet-bridges, the situation is different in European airports, as the use of apron buses is fairly common. Moreover, some of the airline companies have adapted their boarding pass in order to reflect which door one should board once they get down from the bus. While using these buses, the boarding strategies developed in the literature are hard to find their applicability. Thus, a new method for boarding on two-door airplanes when apron buses are used is proposed and tested against the actual boarding method. A model is created in NetLogo 6.0.4, taking advantages of the agent-based modeling and used for simulations. The results show a boarding time reduction of 8.91%

Evaluating Classical Airplane Boarding Methods for Passenger Health during Normal Times

The COVID-19 pandemic has produced changes in the entire aviation industry, including adjustments by airlines to keep the middle seats of airplanes empty to reduce the risk of disease spread. In this context, the scientific literature has introduced new metrics related to passengers’ health when comparing airplane boarding methods in addition to the previous objective of minimizing boarding time. As the pandemic concludes and the aviation industry returns to the pre-pandemic situation, we leverage what we learned during the pandemic to reduce the health risk to passengers when they are not social distancing. In this paper, we examine the performance of classical airplane boarding methods in normal times but while considering the health metrics established during the pandemic and new metrics related to passenger health in the absence of social distancing. In addition to being helpful in normal times, the analysis may be particularly helpful in situations when people think everything is normal but an epidemic has begun prior to being acknowledged by the medical scientific community. The reverse pyramid boarding method provides favorable values for most health metrics in this context while also minimizing the time to complete boarding of the airplane

Determining the Number of Passengers for Each of Three Reverse Pyramid Boarding Groups with COVID-19 Flying Restrictions

The onset of the novel coronavirus SARS-CoV2 has changed many aspects of people’s economic and social activities. For many airlines, social distancing has reduced airplane capacity by one third as a result of keeping the middle seats empty. Additionally, social distancing between passengers traversing the aisle slows the boarding process. Recent literature has suggested that the reverse pyramid boarding method provides favorable values for boarding time and passenger health metrics when compared to other boarding methods with social distancing. Assuming reverse pyramid boarding with the middle seats unoccupied, we determined the number of passengers to include in each of three boarding groups. We assumed that passengers use a jet-bridge that connects the airport terminal to the airplane’s front door. We used agent-based modeling and a stochastic simulation to evaluate solutions. A full grid search found an initial good solution, and then local search optimization determined the best solution based upon the airline’s relative preference for minimizing average boarding time and minimizing risks to previously seated passengers from later-boarding, potentially contagious passengers breathing near them. The resulting solution contained the number of passengers to place into each of the three boarding groups. If an airline is most concerned about the health risk to seated passengers from later boarding passengers walking near them, the best three-group reverse pyramid method adapted for social distancing will first board passengers with window seats in the rear half of the airplane, then will board passengers with window seats in the front half of the airplane and those with aisle seats in the rear half of the airplane, and finally will board the passengers with aisle seats in the front half of the airplane. The resulting solution takes about 2% longer to board than the three-group solution that minimizes boarding time while providing a 25% decrease in health risk to aisle seat passengers from later boarding passengers