Ranking Of Companies Research Articles

Ranking firms based on their financial and diversity performance using multiple‐stage unweighted TOPSIS

AbstractIn this paper, we address the problem of the ranking of companies based on their diversity and financial performance. The addressed problem is a multiple criteria decision‐making problem where a composite measure needs to be obtained to rank firms. Taking as a reference the methodological approach followed by Refinitiv in the construction of their Diversity and Inclusion Index, we propose an alternative ranking framework that overcomes some of the problems identified in the methodological approach of Refinitiv. In particular, the proposed method in this work does not require the a priori establishment of a weighting scheme and is able to incorporate the past behavior of the companies in terms of diversity in their workplaces.

Portfolio Optimization based on the Risk Minimization by the Weight-Modified CVaR vs. CVaR Method

Given the lack of a specific approach to the explanation of values of optimal portfolio weights in the portfolio optimization, the present study aimed to examine large-scale portfolio optimization according to both stock weighting and utilization of SCAD function to minimize the portfolio risk based on the "weight-modified conditional value at risk (CVaR)" and its comparison with the "conditional value at risk (CVaR)" method in the Tehran Stock Exchange. Therefore, the price information of companies listed in the Tehran Stock Exchange and Over-the-counter (OTC) from 2012 to the end of September 2020 was collected, screened, and analyzed daily, and then the risk and return of the portfolios were examined by forming optimal portfolios. The results indicated that the efficiency limit of the stock portfolio and also the ranks of different companies were different according to the types of the optimization method. Based on the behavior of the TEDPIX, the investors' degrees of risk-taking, and the risk management, diversification, and computational complexity of each method, the weight-modified CVaR had a better performance due to better diversification and risk management. Furthermore, the SCAD function added computational complexity to this method.

The effect of pandemic conditions on financial success rankings of BIST SME industrial companies: a different evaluation with the help of comparison of special capabilities of MOORA, MABAC and FUCA methods

Considering COVID-19 pandemic conditions from an MCDM perspective, the change in the ranking positions of the companies before and during the pandemic conditions has become more critical for many researchers and especially financial decision-makers. In this study, different from other studies, a new methodological procedure was followed. For the first time, an MCDM method was chosen among the alternatives with an objective point of view, and the application was continued. In other words, the final performance evaluation is based on the results of this chosen method. In the first step, the financial performance of companies traded in the BIST SME Industry, which is the application area of the study, was calculated with three different MCDM methods (MOORA, MABAC and FUCA). In the second step, the ranking correlations between the calculated financial performance scores and the stock return in the current period were compared with the Spearman method. Finally, in the third step, based on this indirect objective reference verification result (as it is the most appropriate and successful), the necessary financial analyzes were made with the FUCA method. According to the findings, the FUCA method correlated higher with the stock return before and during the pandemic than the other MCDM methods. According to these results, when a performance comparison is made between before and during pandemic conditions, three changes become prominent: the most successful companies, the companies' overall ranking, and the favourite sectors have entirely changed for the base periods. This innovative procedure has been proposed for the first time in the literature and has been successfully applied.

Selection of Coal Transportation Company Based on Fuzzy SWARA-COPRAS Approach

Background: Coal production and marketing enterprises can significantly reduce transportation costs and improve their competitiveness by choosing appropriate road transportation companies. Methods: Based on this, a trapezoidal fuzzy SWARA-COPRAS method is proposed to select coal transportation companies. The trapezoidal fuzzy SWARA method is used to determine the index weight of coal transportation companies. The ranking of coal transportation companies is determined using the trapezoidal fuzzy COPRAS method. Results: Taking a coal production and marketing enterprise in Hubei, China as an example, the application of the trapezoidal fuzzy SWARA-COPRAS method is illustrated, and the coal transportation companies are sorted and analyzed for sensitivity. Conclusions: Compared with the results of other methods, the effectiveness and practicability of the trapezoidal fuzzy SWARA-COPRAS method are verified.

Rehearsal and Performance Volume in Professional Ballet: A Five-Season Cohort Study

Introduction: Few studies have published data concerning the longitudinal rehearsal and performance demands experienced by professional ballet dancers. We aimed to describe the rehearsal and performance volumes undertaken across five professional ballet seasons and identify factors associated with inter-dancer and inter-production variation in dance hours. Methods: Scheduling data were collected from 123 dancers over five seasons at The Royal Ballet. Linear mixed effects models were used to evaluate differences in: 1. weekly dance hours and seasonal performance counts across sexes, company ranks, and months; and 2. factors associated with the variation in rehearsal hours required to stage different productions. Results: On average across the five seasons, a peak in performance volume was observed in December, whereas rehearsal hours peaked in October and November and between January and April. Differences in weekly dance hours were observed between company ranks (p < 0.001, range in means: 19.1 to 27.5 hours per week). Seasonal performance counts varied across company ranks (p < 0.001), ranging from 28 (95% CI: 22, 35) in principals to 113 (95% CI: 108, 118) in the rank of artist. Rehearsal durations were considerably greater in preparation for newly created ballets compared with existing ballets (77.8 vs. 37.5 hours). Rehearsal durations were also greater in preparation for longer ballets, with each additional minute of running time associated with a 0.43 hour increase in rehearsal duration (p < 0.001). Full-length ballets, however, were consistently the most time-efficient to stage due to their long performance runs compared with shorter ballets (16.2 vs. 7.4 performances).Conclusions: Training principles such as progressive overload and periodization should be implemented in professional ballet companies to manage the high and variable rehearsal and performance loads.

Application of MARCOS method in evaluation of efficiency of trade companies in Serbia

The problem of measuring the efficiency of trade companies using methods is continuously relevant, significant and complex. With this in mind, this paper investigates the efficiency of trade companies in Serbia on the basis of the MARCOS method in order to consider the most realistic situation and improve in the future by taking relevant measures. According to the results of the MARCOS method, the top five trade companies in Serbia are in the following order: NELT CO. DOO Belgrade, KNEZ PETROL DOO ZEMUN, DELHAIZE Serbia DOO Belgrade, LIDL Serbia KD NOVA PAZOVA, and MERCATOR-S DOO NOVI SAD. Trade companies in Serbia that sell food products are well ranked. Factors that influenced this ranking of trade companies in Serbia are: general business conditions, interest rate, exchange rate, inflation, sustainable development, inflow of foreign direct investment, employment, living standards, digitalization of business, Covid-19. Also, the application of modern concepts of cost management, customer management, product category management, multi-channel sales, etc. Conducted similar research in other countries provides additional renewal to assess the efficiency of trade enterprises in Serbia and improve in the future by taking relevant measures.

ESG ИНИЦИАТИВА РОССИЙСКИХ КОМПАНИЙ

The article discusses the key evaluation factors when assigning the ESG rating, presents the ESG ranking of Russian companies, analyzes the activities of the top 10 ESG-ranking enterprises.

РИНОК E-COMMERCE: МАРКЕТИНГОВИЙ АНАЛІЗ ЗДОБУТКІВ ТА НАПРЯМІВ РОЗВИТКУ

The article studies the situation and the determination of current trends in the e-commerce market in the world and in Ukraine. Empirical data on the global e-commerce market are taken as a basis and are analysed in terms of size, structure, regional distribution, concentration in market segments. Authors conducted the international ranking of achievements of leading countries in terms of retail e-commerce sales, by type of e-commerce (B2B, B2C) and the ranking of global companies in the e-commerce segment by gross value of goods (GMV). The global retail trade has undergone significant changes due to the constant digitalization of modern business and public life and according to global forecasts for 2025, the total share of e-commerce in retail sales will reach 25%. Significant increase in e-commerce has occurred in both the B2C segment and the B2B segment. Authors revealed that the introduction of social distancing, quarantine and other restrictive measures in response to the COVID-19 pandemic has led to fundamental changes in the structure of global demand and online shopping. Authors have analysed the dynamics of the distribution of sales in the retail segment of e-commerce in the ten leading countries. The United States and China together account for more than 40 percent of all e-commerce sales to both consumers and businesses worldwide, and three of the five largest e-commerce markets are in Asia. Authors determined that the leading e-commerce companies in the B2C segment are mainly based in China and the United States. Online shopping websites have the largest share of online shopping in the world, with Amazon being the undisputed leader in the global ranking of online retail stores in terms of traffic. Authors also note that one of the global trends in e-commerce is the use of mobile devices (m-commerce). The main factors of perspective growth of mobile commerce are determined. The variation of consumer costs by e-commerce by product categories is studied. Authors concluded that the changes in the e-commerce environment are likely to be long-term, given the new waves of the pandemic, the convenience of new consumer shopping habits, saving time, training costs and incentives for companies to gain competitive advantage from investing in new sales channels.

Extending COPRAS Method with Linguistic Fermatean Fuzzy Sets and Hamy Mean Operators

The utilization of linguistic variables is of vital importance for qualitative information processing in mathematical modelling and decision making under uncertainty. The primary purpose of our study is to introduce a novel structure by the fusion of Fermatean fuzzy sets and linguistic term sets. This hybrid structure is termed as the linguistic Fermatean fuzzy set which can be employed for dealing with decision‐making problems involving qualitative information. Several fundamental operations of linguistic Fermatean fuzzy sets are introduced. Furthermore, we present four classes of linguistic Fermatean fuzzy Hamy mean operators, namely, the linguistic Fermatean fuzzy Hamy mean operator, the linguistic Fermatean fuzzy dual Hamy mean operator, the linguistic Fermatean fuzzy weighted Hamy mean operator, and the linguistic Fermatean fuzzy weighted dual Hamy mean operator. Some basic properties of these linguistic Fermatean fuzzy Hamy mean operators are examined as well. In addition, we develop a linguistic Fermatean fuzzy extension of the COPRAS method. We also propose a novel approach to multi‐attribute group decision making with linguistic Fermatean fuzzy information. With our proposed methods, we solve two practical problems regarding food company ranking and green supplier selection, respectively. Finally, the efficacy of our developed method is validated through a comparative analysis with existing methods.

Development of a methodology for evaluating the effectiveness of financial policies of companies

Subject. This article presents an analysis of the essence of financial policy as a factor of effective development of companies. Evaluation of the effectiveness of the implemented financial policy of companies is a significant scientific and practical problem. It determines the choice of the main criteria used to calculate the financial policy effectiveness. Objectives. The article aims to develop a comprehensive methodology for assessing the effectiveness of financial policy of companies in modern conditions, and define criteria for its evaluation. Methods. The Due Diligence approach is the basis for solving the research tasks: comparing the current standards and methods for assessing the financial policy of companies and simplifying its implementation through the proposed method of multivariate coefficient analysis. Results. The article offers a comprehensive approach to assessing the effectiveness of financial policy, considering electric power companies as a case study. The practical significance of the results obtained lies in the use to increase the investment attractiveness of companies that are considered as potential investment objects. Conclusions. The research proposes a methodology for assessing the financial policy of companies based on a multivariate, customizable system of financial coefficients. An indicator of the effectiveness of financial policy of companies was calculated. It can be recommended for practical application. The obtained results of evaluating the effectiveness of financial policy can be used by the companies’ management to make management decisions, investors to choose the best investment option, market participants to rank companies by efficiency, and determine industry benchmarks.

MODERN APPROACHES TO ENTERPRISE CORPORATE SOCIAL RESPONSIBILITY EVALUATION

Purpose. Corporate social responsibility (CSR) is an important feature of modern business. It provides a certain level of voluntary response to social problems, compliance with moral requirements of society. Companies have already realized the benefits of a socially proactive position and are increasingly involved in solving social and environmental problems. This raises the issue of CSR evaluation from a cost / benefit standpoint. The aim of the article is to study the existing approaches to assessing the level of CSR and determine the scope of their use. Design/methodology/approach. Abstract and logical method was used for generalization of theoretical and methodological provisions for the assessment of CSR. A systematic approach was used to form a system of ESG-indicators and to develop a system of indicators for assessing the benefits of implementing CSR activities. Economic and statistical methods were used for the assessment of CSR Ukrainian companies. Finding. The article presents the key characteristics of CSR. The focus is on the positive impact of the implementation of CSR practices on the activities of companies. A critical analysis of the approaches of Ukrainian scientists to the assessment of CSR was made, which allows to distinguish the assessment of CSR in general and the effectiveness of CSR activities. The authors identified three methodological approaches to the assessment of CSR. A general description of these approaches is given, their advantages and disadvantages are identified. The authors note that there is no universal form of financial reporting, businesses have a choice of what form it is. The most common are sustainable development reports, which are formulated for GRI standards. More Ukrainian companies publish their social reports, thus declaring their commitment to CSR concepts. It is proved that CSR is gradually transformed into a system of environmental, social and management parameters - ESG. The content of ESG-factors is determined and a system of indicators in the context of ecological, social and management spheres is formed. The system of indicators for assessing the benefits of implementing CSR activities is formed. A special place in the article is given to the international rankings of companies according to their ESG indicators. Based on the data of the catalog of social initiatives of companies, the general state of CSR in Ukraine is analyzed. It is established that the development of CSR in Ukraine is in line with European trends. The modern practice of social responsibility assessment is systematized. Practical implications. The practical significance of the obtained results is to develop the theoretical and methodological basis for the assessment of CSR. The results of the study can be used by entrepreneurs and managers seeking to achieve long-term success in the global business environment. Originality/value. The theoretical basis of CSR evaluation is developed by distinguishing three groups of methodological approaches, including analysis of non-financial reporting, calculation of quantitative and qualitative indicators, as well as index and rating methods. A system of indicators based on the maximum consideration of stakeholders' interests has been developed to assess the benefits of CSR activities.

An Integrated DEA and PROMETHEE II Method for Complete Ranking: An Application in Life-Insurance Sector

Globally, insurance and takaful companies play a crucial role in economic and financial development of a country. Malaysia’s insurance sector has undergone substantial changes compared to two decades ago. Due to intense competition observed in Malaysian insurance industry, efficiency measurement and a complete efficiency ranking of insurance companies are very important for the decision makers so that necessary changes and improvement can be made. Data Envelopment Analysis (DEA) is a non-parametric method that has been acknowledged as an effective method to measure the efficiency of homogeneous decision-making units (DMUs). The main advantage of DEA is its ability to handle multiple inputs and outputs. However, standard DEA has poor discrimination power since it generates too many efficient units especially when the number of DMUs under study is insufficient in comparison to number of inputs and outputs. It cannot discriminate efficient units and therefore unable to give a complete ranking of DMUs. This study aimed to overcome the ranking problem found in standard DEA by integrating DEA and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) II. The hybrid method was applied to evaluate the efficiency and ranking of 22 life insurance and takaful companies in Malaysia from the period of 2017 to 2018. Input variables used in this study comprised of fees and commission, and management expenses. Meanwhile, output variables were net premium and generated investment income. The proposed method involved two stages. In the first stage, DEA was applied to obtain the efficient scores for the DMUs. In the second stage, PROMETHEE II was implemented to rank the efficient units. This hybrid method has successfully obtained full ranking of all the insurance companies under study. The inefficient companies can learn strategies and practices from efficient companies to enhance their services. It is recommended for future research to integrate DEA with other Multi Criteria Decision Making (MCDM) methods such as TOPSIS and VIKOR to fully rank the DMUs.

Investment Appeal of Modern Electric Power Generating Companies

Nowadays, the conditions for the further reforming of Russian electric power industry and developing its generating companies are changing. However, the problems of attracting investments into this sphere and increasing the investment appeal of the involved companies remain unsolved. The purpose of the research is to assess the investment appeal of the modern wholesale and territorial companies generating electric power, mainly for portfolio investors. The assessment was primarily conducted using the method of financial ratios, taking into consideration the approach used by A. Zaporozhan, A. Petrova and M. Kalvarskaya for assessing investment appeal of generating companies at the initial stage of the reforming of Russian electric power sector. Specific amendments to this approach are suggested. These amendments concern the increase of the number of the assessed objective financial indicators and specification of their content. Componentwise ranking of companies according to their investment appeal was conducted. It allowed the author to identify leaders and outsiders. One can observe comparability of the obtained results with the assessment of the investment appeal of generating companies as far as the quality of their corporate management is concerned, conducted by the center for corporate development ТopCompetence, Association of Independent Directors and National Research University «Higher School of Economics».

Рэнкинг крупнейших групп и компаний в области аутсорсинга учетных функций: итоги 2020 года

As the next, twelfth ranking of the largest companies in the field of outsourcing of accounting functions from RAEX shows, this sector of the services market ended in 2020 with the worst dynamics for the entire period of observation - in fact, stagnation. Outsourcing providers pin their hopes for growth with the business learning lessons from working in a pandemic.

Company Ranking Prediction Based on Network Big Data

With the advent of the era of big data, it has become one of the important tasks of data mining to utilize the massive info on the internet to realize the forecast of relevant aspects. In recent years, some scholars have studied how to use company’s information for the revenue or stock forecasts, but there is very little research on inter-company ranking predictions. So from the perspective, this paper brings in the Learning-to-Rank (LtR) method into the corporation ranking prognostication, and proposes the Company Ranking Prediction Model (CRPM) grounded on LtR. First, obtain the information on the Fortune 500 official website and other correlative sites. Through data analysis, data cleaning, ranking processing, label division and data formatting, a brand-new corporation data-set containing four major categories of features (10 characteristics in total) is constructed. Then bring in four commonly utilized LtR approaches, employing the previously created data-set to train different models. Finally, each model is evaluated by the two information retrieval metrics, normalized discounted cumulative gain and mean average precision. The experimental results show that the assessment best-performing model CRPM-LambdaMART and CRPM-RandomForests can tellingly forecast the ranking of Fortune 500 companies in the next year, which has certain practical value for financiers to reasonably planning their investments and corporation managements to legitimately programming their strategic deployments.

Sustainable Recovery: The Multiple Benefits of Collaboration

The oil and gas industry is recovering along with the health situation and the world’s economy following one of the largest downturns in its 160-year history caused by the COVID-19 pandemic. What comes ahead brings its own challenges. The recent Intergovernmental Panel on Climate Change’s (IPCC) Working Group 1 contribution to the IPCC’s Sixth Assessment Report, Climate Change 2021: The Physical Science Basis, published in August, highlighted the “widespread and rapid acceleration of climate change,” with the 1.5°C threshold reached as early as the end of this decade. The dramatic weather events around the globe this summer (in the Northern Hemisphere) with historical temperature records on the North American Pacific Coast and in the central and eastern Mediterranean regions, and huge fires impacting those regions and others such as Siberia, were a reminder that the transformation is occurring now. In this context, the energy mix that the world uses today needs to evolve to a more rational use through energy efficiency and with a lower carbon content, starting from the use of coal. The oil and gas industry has been pioneering the development of technologies such as carbon capture and underground storage and blue hydrogen. International oil companies and national oil companies rank amongst the largest technology investors in renewables and energy storage. Renewables also have a strong potential in applications such as steam injection. Collaboration among the industry and with other peripheral sectors will be an essential ingredient to accelerate the transformation of the energy sector. I personally started in the oil and gas industry more than 4 decades ago in research and development (R&D) with a large oilfield service company, where I led a team of scientists investigating hydraulic fracturing. One of the projects was related to acid fracturing, which required the injection of a viscous non-Newtonian pad to fracture the formation and keep the fracture open, followed by acid which had a much lower viscosity. The two-fluid displacement inside the fracture led to an instability called viscous fingering. In order to understand the phenomenon, we put together a very diverse team, comprising a mathematician, an astrophysicist, a physicochemist, and a geologist. The team was unable to initially work well together and collaborate. The breakthrough came when a high-level scientist from Boston University, a specialist in critical phenomena, was added as a catalyst to the team. Within a few months, the team managed to develop and validate a model for viscous fingering using diffusion-limited aggregation and fractal theory, and its work was published in Nature and the American Physical Society’s Physical Reviews Journals. The team then developed a new set of models for wormholes created by the injection of acid through matrix acidizing and fracture acidizing which were used to create the required chemistry to ensure effectiveness of the treatments. I remain convinced that if we had not included the diversity of the skills and used a catalyst for collaboration, we would not have cracked the research code so rapidly.

Applying Complementary Credit Scores to Calculate Aggregate Ranking

Researchers have been improving credit scoring models for decades, as an increase in the predictive ability of scoring even by a small amount can allow financial institutions to avoid significant losses. Many researchers believe that ensembles of classifiers or aggregated scorings are the most effective. However, ensembles outperform base classifiers by thousandths of a percent on unbalanced samples.
 This article proposes an aggregated scoring model. In contrast to previous models, its base classifiers are focused on identifying different types of borrowers. We illustrate the effectiveness of such scoring aggregation on real unbalanced data.
 As the effectiveness indicator we use the performance measure of the area under the ROC curve. The DeLong, DeLong and Clarke-Pearson test is used to measure the statistical difference between two or more areas. In addition, we apply a logistic model of defaults (logistic regression) to the data of company financial statements. This model is usually used to identify default borrowers. To obtain a scoring aimed at non-default borrowers, we employ a modified Kemeny median, which was initially developed to rank companies with credit ratings. Both scores are aggregated by logistic regression.
 Our data Russian banks that existed or defaulted between July 1, 2010, and July 1, 2015. This sample of banks is highly unbalanced, with a concentration of defaults of about 5%. The aggregation was carried out for banks with several ratings.
 We show that aggregated classifiers based on different types of information significantly improve the discriminatory power of scoring even on an unbalanced sample. Moreover, the absolute value of this improvement surpasses all the values previously obtained from unbalanced samples.
 The aggregated scoring and the approach to its construction can be applied by financial institutions to credit risk assessment and as an auxiliary tool in the decision-making process thanks to the relatively high interpretability of the scores.

Measuring the quality of service of water companies: A two-stage goal programming synthetic index proposal

Quality of service (QS) is one of the most important parameters for evaluating the performance of water companies. It is a multidimensional concept that encompasses several performance indicators, with synthetic indicators that provide useful evaluation tools. Drinking water provision and wastewater treatment are basic services for which there is a series of minimum requirements that all water companies must meet. Under this premise, this study proposes a novel synthetic indicator to evaluate the QS of water companies in two stages. First, the non-compliance index was estimated, which provides information on the degree of non-compliance for essential indicators. Second, based on the goal programming approach, each water company's strengths and weaknesses were computed to generate a QS index with rankings. The index was then tested empirically on a sample of 24 water companies in Chile based on 10 initial indicators (of which three are considered essential indicators). Overall, 37.5% of the water companies did not meet the thresholds delineated for the essential indicators. Moreover, only five water companies had a positive QS index (i.e., their strengths were greater than their weaknesses). A scenario analysis evaluated the impact of weight allocation on the QS of water companies and their ranking. The ranking of water companies varied depending on the weights allocated to the initial indicators, demonstrating the importance of delineating regulator preferences when assessing QS.

Assessing the healthiness of UK food companies' product portfolios using food sales and nutrient composition data.

The provision and over-consumption of foods high in energy, saturated fat, free sugars or salt are important risk factors for poor diet and ill-health. In the UK, policies seek to drive improvement through voluntary reformulation of single nutrients in key food groups. There has been little consideration of the overall progress by individual companies. This study assesses recent changes in the nutrient profile of brands and products sold by the top 10 food and beverage companies in the UK. The FSA/Ofcom nutrient profile model was applied to the nutrient composition data for all products manufactured by the top 10 food and beverage companies and weighted by volume sales. The mean nutrient profiling score, on a scale of 1-100 with thresholds for healthy products being 62 for foods and 68 for drinks, was used to rank companies and food categories between 2015 and 2018, and to calculate the proportion of individual products and sales that are considered by the UK Government to be healthy. Between 2015 and 2018 there was little change in the sales-weighted nutrient profiling score of the top 10 companies (49 to 51; p = 0.28) or the proportion of products classified as healthy (46% to 48%; p = 0.23). Of the top five brands sold by each of the ten companies, only six brands among ten companies improved their nutrient profiling score by 20% or more. The proportion of total volume sales classified as healthy increased from 44% to 51% (p = 0.07) driven by an increase in the volume sales of bottled water, low/no calorie carbonates and juices, but after removing soft drinks, the proportion of foods classified as healthy decreased from 7% to 6% (p = 33). The UK voluntary reformulation policies, setting targets for reductions in calories, sugar and salt, do not appear to have led to significant changes in the nutritional quality of foods, though there has been progress in soft drinks where the soft drink industry levy also applies. Further policy action is needed to incentivise companies to make more substantive changes in product composition to support consumers to achieve a healthier diet.

Choosing an Insurer

This paper is about how customers can choose an insurance company for taking insurance policies based on its financial position. In some market such as in India, the ranking of the insurance companies are based on new business but this paper also gives other variables to select.