Competitiveness and Financial Management in SMEs Hotel Businesses in Yucatan, Mexico

Small and medium hotel enterprises in Yucatan represent an important sector for the economic development of the State. However, inadequate financial management leads to reduced profits and a short life expectancy for them. In the case of financial management in hotels, it is necessary to develop an indicator model that facilitates the reading of the results, of the financial situation of the hotels, and of the organization in general. It is necessary to obtain hard data that lead to making quick and forceful decisions in a timely manner. The objective of this study is to explain why a good financial management is a factor that greatly increases the competitiveness of organizations and that hotel financial management indicators are an instrument for measuring the different variables associated with organizational objectives, expressed in terms of some quantitative basis that defines the scope or achievement of the expected results. For this work, a bibliographical review of relevant articles from a range of authors was conducted.

A Multidimensional Comparative Analysis of Involvement in CSR Activities of Energy Companies in the Context of Sustainable Development Challenges: Evidence from Poland

In recent years, corporate involvement in CSR has become increasingly important and appreciated in the context of the ideas and assumptions regarding sustainable development. Due to the specificity of the energy sector, its particular impact on the environment, the living conditions of the population, and the social involvement of energy companies is particularly desirable, therefore it is observed and assessed by many stakeholder groups. The aim of this article is to assess the CSR commitment of Polish energy companies listed on the Warsaw Stock Exchange. The assessment was based on the proposed indicator model, based on the data published in the annual reports of the companies. The study uses data from the years 2016–2020. The main research question is as follows: What is the engagement in CSR activities of six Polish energy companies towards contractors, investors, employees, society, and the environment? The obtained results show that the investigated energy companies present a similar average level of engagement in CSR activities. The highest level of involvement concerns the area of contractors and the lowest levels relate to the donors of capital and the environment.

Structured Evaluation of Rehabilitation Programs Outcomes in Psychiatry: Application of a Recovery-Centered Model

Rehabilitation is oriented to psychiatric patients’ recovery through specific techniques and structured projects, not yet fully standardized, carried out in territorial services. This study aims to apply an operational structured outcome indicator model (hospitalizations, continuity of care, LAI treatment adherence, working support) through a recovery-centered model in a rehabilitation community in Milan. This observational-retrospective study included 111 patients from a University High Assistance Rehabilitation Community (C.R.A.) based in Milan. Psychopathological and psychosocial functioning was evaluated with Kennedy Axis V, Brief Psychiatric Rating Scale (BPRS), Life Skills Profile (LSP), AR module of the VADO scale. Statistical analyses were performed using SPSS software version 19. Student t test and Wilcoxon Test were used to analyze quantitative variables, while McNemar test for qualitative variables. The minimum level of significance was set at 0.05 (p <0.05). The results showed that CRA rehabilitation program led to significant improvement in global functioning in terms of hospitalization reduction; improved continuity of care; stable adherence to psychopharmacological treatment with Long Acting Injectable (LAI) antipsychotics; stable employment maintenance during the year following discharge from the CRA. This study confirmed the utility of a structured outcome indicator model and highlighted its feasibility in daily clinical context of a rehabilitative community. Our results supported the effectiveness of a community-based rehabilitation program to improve individual functioning and clinical stability. However, further studies are required to better achieve the development of a recovery-oriented rehabilitation model and rigorously define an outcomes evaluation model.

A Dynamic Level Technical Indicator Model for Oil Price Forecasting

Investment in commodities and stock requires a nearly accurate prediction of price to make profit and to prevent losses. Technical indicators are usually employed on the software platforms for commodities and stock for such price prediction and forecasting. However, many of the available and popular technical indicators have proved unprofitable and disappointing to investors, often resulting not only in ordinary losses but in total loss of investment capital. We propose a dynamic level technical indicator model for the forecasting of commodities’ prices. The proposed model creates dynamic price supports and resistances levels in different time frames of the price chart using a novel algorithm and employs them for price forecasting. In this study, the proposed model was applied to predict the prices of the United Kingdom (UK) Oil. It was compared with the combination of two popular and widely accepted technical indicators, the Moving Average Convergence and Divergence (MACD) and Stochastic Oscillator. The results showed that the proposed dynamic level technical indicator model outperformed MACD and Stochastic Oscillator in terms of profit.

RAPOT: An Adaptive Multifactor Risk Assessment Framework on Public Opinion for Trial Management

Since public opinion from social media has a growing impact and supervision on trial, risk assessment on public opinion is increasingly important in refined trial management. However, the tremendous amount of public opinion and the insufficient historical logs of trial procedures bring challenges to risk assessment on public opinion. To address this, we propose an adaptive multifactor risk assessment framework on public opinion with fuzzy numbers. Initially, we establish a multilayer indicator model for assessing the risk of public opinion (POR) with multilayer analysis and decision methods. Then, we explore the association rules hidden in the process logs to update the indicator model periodically. Moreover, we design a public opinion analysis module for indicator evaluation, including analysis in public opinion sentiment, hot search, and social media coverage to deal with big data on social media. Especially, the public opinion sentiment is classified by topic-based BiLSTM (T-BiLSTM), which is more accurate. Finally, the fuzzy number similarity is employed to determine POR’s level in the nine-level risk system. Experimental results validate the efficiency of our framework when assessing the POR.

A Robust Fuzzy Decision Making on Global Warming

Background: In this article we develop a global warming indicator model under fuzzy system. It is the light of sun that environmental pollution is responsible for the cause and immediate effect of global warming. Limited amount of oxygen in the air, continuous decrease of fresh water volume, more especially the amount of drinking water and the rise of temperature in the globe are the major symptoms (variants) of global warming. Thus, to capture the facts we need to develop a mathematical model which has not yet been developed by the earlier researchers. Introduction: An efficient literature survey has been done over the three major parameters of the environment namely oxygen, fresh water and surface temperature exclusively. In fact we have accumulated 150 years-data structure for these major components and have analyzed them under fuzzy system so as to develop an efficient global warming indicator model. Method: First of all, we gave few definitions on fuzzy set. Utilizing the data set we have constructed appropriate membership functions of the three major components of the environment. Then applying goal programming problem, we have constructed a fuzzy global warming indicator (GWI) model subject to some goal constraints with respective priority vectors (Scenario 1 and Scenario 2). An extension has also been included for multi-valued goal programming problem and numerical illustrations have been done with the help of LINGO software. Result: Numerical study reveals that the GWI takes maximum and minimum values in a decreasing manner as time increases. It is seen that for scenario 1, the global environmental system will attain its stability after 30 years by degrading 31% of GWI with respect to present base line. For scenario 2, after the same time the global environmental system will attain its stability quite slowly by degrading 28% of GWI with respect to present base line. Conclusion: Here we have studied a mathematical model of global warming first time using fuzzy system. No other mathematical models have been existed in the literature. Thus, the basic novelty lies in a robust decision-making approach which shows the expected time of extinction of major species in this world. However, extensive study on data analytics over major environmental components can tell the stability of the global warming indicator and hence the future fate of the globe also.

Construction of an Industry Cycle Indicator for Profitability Prediction Analysis of Aggregate Firms in Bangladesh

Purpose of this study: In the aggregate industrial sector, government intervention to influence demand within the economy is generally counterproductive, while the optimal policy is to concentrate on supply-side reforms that help the economy become efficient. The objective of this study was to construct a unique industry cycle indicator for Bangladeshi aggregate firms within this industrial sector. The specific objectives were to assemble a unique industry cycle indicator which recommends early signals of a firm’s industrial vulnerability, identify industry cycle indicator turning points and evaluate the predictive performance of the industry. The industry cycle indicator model demonstrates the macroeconomic fluctuations in the industrial sector. Methodology: The industry cycle indicator was constructed following the approach of the Conference Board (2000). The result wasthen tested for robustness with a macro-stress test. Lagged independent variables were used in this study to allow early predictions by the ICI for the year in which the financial crisis happened. Main Findings: The industry cycle indicator model underplays the role of aggregate industrial efficiency in influencing the economic cycle. By forecasting directional changes, this leading indicator allows policymakers to be made aware of revolutions in the financial industry and to undertake early precautionary steps to prevent vulnerability. Here, the constructed industry cycle indicator demonstrates a remarkable lead time of around 6 months for predictions and outperforms by the leading against the reference series. Research Limitations/Implications: The industry cycle indicator model rejects the Keynesian approach and also rejects monetarism. It tends to be associated with neo-classical economics. The ICI generally assumes that shocks to productivity lead to economic fluctuations. In other words, a temporary fall in output is an inevitable consequence of a drop in productivity within the industrial sector. It also leads to adjustments to this new equilibrium and enables resources to discover more productive uses. Novelty/Originality: This research demonstrates that enhanced knowledge of components of the macro-prudential policy framework combined with the existence of a certain degree of standardisation of the macro-prudential tools and indicators is essential. This can significantly develop the capability of the financial markets supervisory authorities to forecast systemic risk and to avoid or reduce the consequences of industrial crises. The present study reflects a situation for upcoming researchers who intend to study and develop their interests in this area.