Profitability Risk Research Articles

Managing Financial Risks of Global Companies Through Corporate Social Responsibility: The Specifics of Sustainable Employment in Developed and Developing Countries

The motivation for this research was the desire to disclose the social nature of the financial risks of global companies: the authors attempted a scientific explanation of the influence of corporate social responsibility, which is manifested through the preservation and creation of additional jobs, on the financial risks of global companies. The research aims to establish the interdependence between financial risks and sustainable employment in global companies. This goal is achieved using the SEM (structural equation modeling) method based on corporate statistics from the Fortune “Global 500” rankings for 2021–2023. As a result, the consequences of global companies’ CSR (corporate social responsibility) practices in personnel management and financial risk management are modeled and described through quantitative and qualitative patterns. The established regularities proved that for developed and developing countries, the larger the number of employees, the lower the financial risks of global companies—the risk of a decrease in profitability, the risk of loss of profit, and the risk of depreciation of assets. The main conclusion is that there is a close systemic relationship between the financial risks of global companies and their workforce size, suggesting that CSR is key to highly effective financial risk management. A clear distinction between the practices of financial risk management through CSR in developed and developing countries forms the basis of the theoretical significance of the research results. The authors provide recommendations to improve the current practice of financial risk management in global companies by integrating it more closely with personnel management practices, highlighting their managerial relevance. It is proposed that corporate strategies for global companies in developed countries should focus on reducing the risk of declining profitability, as CSR has the most pronounced and consistent impact on this particular financial risk. In developing countries, corporate strategies are recommended to be structured by diversifying the areas of CSR application, with the most promising in financial risk management being the reduction in asset depreciation risk and the reduction in profitability risk. The findings of this research have practical significance because they enhance the predictability of CSR activities of global companies and open up opportunities for highly accurate forecasting of the financial risk implications of ensuring sustainable employment by global companies, considering the specificities of developed and developing countries.

Manajemen Risiko Usahatani Cabai Rawit: Studi Kasus Di Kawasan Gunung Merapi

Cayenne pepper (Capsicum frutescens L) is a common horticultural commodity cultivated by farmers in the Mount Merapi area. Farmers in this region face the risk of fluctuating productivity due to unpredictable volcanic eruption activities. This study aims to describe the types, sources, and levels of risk, analyze and examine risk management in bird's eye chili farming based on risk levels, risk mapping, and the total household income analysis of bird's eye chili farmers in Mount Merapi. The sample consists of 100 farmers selected through simple random sampling, with the criteria being residents who have been farming cayenne pepper for 10 years in the Mount Merapi area, growing cayenne pepper as the main commodity on their farmland, and farmers with and without additional income sources outside of farming. Data analysis includes risk analysis, total household income analysis, and descriptive quantitative analysis. In Pakem Subdistrict, the coefficient of variation values for production, price, and profit risks are 0.67, 0.08, and 1.20, respectively. In Dukun Subdistrict, these values are 0.55, 0.14, and 2.40, respectively. Lastly, in Selo Subdistrict, the values are 0.45, 0.07, and 0.84, respectively. Household income analysis is divided into two categories: farmers with additional income sources outside of farming and those without additional income sources in each district. The highest average total household income of cayenne pepper farmers is found in Selo Subdistrict. Important considerations in agricultural risk management include providing insurance for cayenne pepperi, market development, and land diversification.

Evaluation of alternative farm safety net program combination strategies

PurposeSeveral farm safety net strategies are available to farmers as a source of financial protection against losses due to price instability, government policies, weather fluctuations and global market changes. Producers can employ these strategies combining crop insurance policies with countercyclical policies for several crops and production areas; however, less is known about the efficiency of these strategies in enhancing profit and reducing its variability. In this study, we examine the efficiency of these strategies at minimizing inter crop year farm profit variability.Design/methodology/approachWe utilized relative mean of profit and coefficient of variation, to compare counterfactually calculated farm safety net strategies for a sample of 28,615 observations across 2,486 farms and four dryland crops (corn, soybean, sorghum and wheat) in Kansas spanning nine crop years (2014–2022). A no farm safety net strategy is used as the benchmark for every alternative strategy to ascertain whether a policy customization is statistically different from a no farm safety case.FindingsThe general pattern of the results suggests that program combination strategies that have a high-profit enhancement potential necessarily have low profit risk for dryland wheat and sorghum production. On the contrary, such a connection is absent for dryland corn and soybeans production. Low-cost farm safety net strategies that enhance corn and soybeans profits do not necessarily lower profit risks.Originality/valueThis paper is one of the first to use a large sample of actual farm-level observations to evaluate how combinations of safety net programs offered under the Title I (PLC, ARCCO and ARCIC) and XI (FCIP) of the U.S. Farm Bill rank in terms of profit level enhancement and profit risk reduction.

Corporate Accounting Management Risks Integrating Improved Association Rules and Data Mining

With the development of the times, enterprises need to face more data in operational decision-making. Traditional data analysis strategies cannot handle the growing amount of data well, and the accuracy of analysis will also decrease when faced with uneven data types. The research uses a corporate accounting management risk analysis technology that combines big data algorithms and improved clustering algorithms. This method combines big data processing ideas with a clustering algorithm that incorporates improved weighting parameters. The results show that on the data sets DS1, DS2, and DS3, the NMI values of the GMM algorithm are all 0; while the NMI values of the MCM algorithm correspond to 0.9291, 0.9088 and 0.8881 respectively. At the same time, the Macro-F1 values of the Verify2 algorithm correspond to 0.9979, 0.9501, and 0.9375 respectively, and the recognition accuracy of the data remains above 85%. In the running time comparison, when the number of samples in the data set reaches 5,000, the calculation time of the Verify2 algorithm remains within 5 seconds. In terms of practical application results, the study selected the profitability risk indicators of 40 companies for analysis. After conducting risk ratings, it can be seen that companies No. 5, 6, 7, and 39 have the highest risk levels, and companies No. 33 and 34 have the highest risk levels. The lowest level. After conducting risk assessments on the 40 selected listed companies, the risk level of net asset income of each company remained at level 5, and the risk level of earnings per share remained at level 3. The above results show that this technology has good performance in terms of calculation accuracy and calculation time, can assess enterprise risks, and can provide data support for enterprise operation decisions.

Risk Transmission in Low-Carbon Supply Chains Considering Corporate Risk Aversion

In order to study the impact of risk aversion characteristics of enterprises on supply chain risk transmission, the risk aversion utility function is introduced, and the risk elasticity coefficient is used to construct a supplier-dominated low-carbon supply chain risk transmission model. Simulation analysis is conducted to investigate the transmission of emission reduction and revenue risks caused by internal and external contingent risk factors. The study reveals that under conditions of market demand uncertainty, the risk transmission effect is unaffected by the risk aversion characteristics of members in the low-carbon supply chain. While the risk-aversion characteristics of suppliers can decrease their own profit risk, they have a negative effect on the profit risk of manufacturers and the emission reduction risk of supply chain nodes. There exists a critical threshold for the impact of the risk-aversion degree of suppliers on their own emission reduction risk transmission effect. When this threshold is exceeded, the emission reduction risk decreases with increasing risk aversion intensity of suppliers, and vice versa. The risk aversion characteristics of manufacturers can weaken the negative effect of supplier risk aversion on the fluctuation risk of manufacturer profits, but they exacerbate the emission reduction risk transmission effect of manufacturers under asymmetric information influence. The findings have important theoretical and practical implications for supply chain risk management.

Assessing Profit Risk Prognosis in Industrial Enterprises

Assessing Profit Risk Prognosis in Industrial Enterprises

Assessing the risk of profit shifting among the suppliers to Danish municipalities

PurposeAn increasing number of Danish municipalities wish to minimize tax avoidance due to profit shifting in their public procurement. To facilitate this effort, this study aims to develop a firm-level indicator to assess the potential risk of profit shifting (PS-risk) from Danish subsidiaries of multinational corporations to subsidiaries in low-tax jurisdictions.Design/methodology/approachDrawing from previous research, PS-risk is assumed to depend on the maximum difference in the effective corporate tax rate between the Danish subsidiary and other subsidiaries under the global ultimate owner, in conjunction with the tax regulations relevant to profit shifting. The top 400 contractors in Danish municipalities from 2017 to 2019 are identified and their relative PS-risk is estimated by combining information about corporate ownership structure with country-specific information on corporate tax rates, tax regulations and profit shifting from three independent data sets.FindingsThe PS-risk estimates are highly significantly positively correlated across the data sets and show that 17%–23% of the total procurement sum of the Danish municipalities has been spent on contracts with corporations having a medium to high PS-risk. On average, PS-risk is highest for large non-Scandinavian multinational contractors in sectors such as construction, health and information processing.Social implicationsDanish public procurers may use the indicator to screen potential suppliers and, if procurement regulations permit, to ensure high-PS-risk bidders document their tax practices.Originality/valueThe PS-risk indicator is novel, and to the best of the authors’ knowledge, the analysis provides the first estimate of PS-risk in Danish public procurement.

Bonus or Penalty? Designing Service-Level Agreements for a Decentralized Supply Chain: The Implication of Return on Investment

We study the coordination of two-echelon supply chains via service level-dependent bonus and penalty contracts and assume that the manufacturer maximizes its profit while enabling the supplier to achieve its performance target. Profit and return on investment (ROI) are considered as the supplier’s performance measures. We compute optimal contract parameters and perform a numerical study. In addition, we perform a simulation-based study to analyze the profit risk of the considered parties. For supplier profit targets, bonus and penalty contracts lead to the same profit for both parties, but bonus contracts lead to lower costs, hence, a higher ROI. For supplier ROI targets, bonus contracts always lead to higher manufacturer profit, and no optimal penalty contracts exist. For every contract service level, optimal bonus contracts exist that maximize profit and ROI of the manufacturer simultaneously. Thus, we analyze the profit risk for the manufacturer and the supplier and show that it can be significantly reduced by setting an appropriate contract service level. The manufacturer usually should prefer bonus contracts. They allow to optimize profit and ROI simultaneously and even offer an additional degree of freedom to reduce the profit risk.

On estimation of losing of the risk of profit of industrial enterprises

On estimation of losing of the risk of profit of industrial enterprises

Diffusion of ESG Behavior Improvement Strategy for New Energy Enterprises under Weighted Benefit Risk Mechanism ——Based on Complex Network Evolution Game

In order to explore the impact of the enterprise's right, responsibility and profit risk mechanism on the enterprise's ESG behavior improvement strategy in the context of carbon emission reduction, this study uses Matlab to build a new energy enterprise cooperation game network model and establish the NW small world initial network. According to the process and result of multi-agent complex network game, this paper analyzes the strategic choice and development factors of ESG behavior in new energy enterprises. It is found that when the awareness of executives increases, the profits of enterprises will increase, but the spread of ESG behavior improvement is not significant; When the competitive intensity of enterprises increases, the profits of enterprises with ESG behavior improvement will decrease, and the diffusion of ESG behavior improvement strategy will be slow. When the price of carbon trading increases, the income of enterprises adopting ESG behavior will increase, but the sensitivity of carbon trading price to the expansion of enterprise network is not significant.

Financial Risk Management of FK Coal Group: Basis for Policy and Strategy Formulation

This study delves into the financial risk management of FK Coal Group in China, focusing on aspects such as credit risk, liquidity risk, stability risk, and profitability risk. The research aims to provide a comprehensive profile of FK Coal Group, including its organizational structure, years in operation, number of employees, geographical scope, and asset size as of 2022. The financial risks are primarily associated with debt payments, asset management, the company's capacity to meet expenses, and production costs and outputs. The financial risk management process encompasses risk identification, analysis, evaluation, and treatment. Challenges are encountered in each phase, such as uncertain adverse events, risk assessment accuracy, risk mitigation strategies, and risk reduction and avoidance measures. The survey results from the employees of FK Coal Group reveal that it is a state-owned enterprise with a long operational history, a substantial workforce, and strong assets, primarily operating in the domestic and international markets. The study underscores the critical role of financial risk management in ensuring the company's operational continuity and competitiveness. Effective risk planning and monitoring are highlighted as crucial elements to improve profitability and prevent excessive spending or losses. The proposed financial risk management policy or strategy aims to address these challenges comprehensively, focusing on proactive risk identification, thorough risk analysis, robust risk evaluation, and appropriate risk treatment strategies to minimize adverse impacts on FK Coal Group's financial health and performance.

Evaluation of Offshore Project Development under Two Fiscal Regime in Indonesia

The general characteristics of deep water offshore field development are the uncertainty of geological conditions, high technology requirements and development costs, and volatility of oil and gas prices. Despite these challenges, the development of a deep water offshore field remains a strategic project for sustainable economic growth. This study will evaluate the impact of current fiscal of the three offshore field development and estimates the limits of oil and gas price, reserves, and expenses. The intention is to obtain the optimal conditions to encourage the development of new offshore fields. The approached will used a discounted cash flow modelling, followed by evaluate the profitability risk using deterministic and stochastic sensitivity analysis. Monte Carlo simulation used to take into account the uncertainty of several variables, such as oil and gas prices, operating costs, development costs, and reserves. The result shows that investment decisions for the development of new and/or extensions fields in offshore areas remain quite challenging economically, considering to the high development and operating costs, as well as fluctuating of oil and gas prices. The opportunity to obtain a positive net present value on new deep water offshore development fields is less than 41%, thus indicates that further initiative of cost efficiency and fiscal incentive is required in preparing investment planning of new deep water offshore field to compensate the high development and operational cost.

Inventory and financial strategies of capital‐constrained firms under limited joint liability financing

This paper studies the operations and financial decisions of two capital‐constrained firms via a limited joint liability (LJL) financing scheme offered by a bank with a menu of loan terms including interest rate and leverage ratio/credit line. To explicitly assess the value of LJL financing, we assume that the firms either use LJL financing scheme or traditional individual financing scheme to finance their operations. Under LJL financing scheme, we construct a non‐cooperative game model in which the two firms separately determine their own inventory decision to serve random demand, according to the prior joint liability agreement between the two firms and the bank. We prove that the non‐cooperative game between the two firms under the LJL financing scheme is a supermodular, and thus establish the existence of equilibrium inventory decisions of the firms. We then characterize the optimal loan terms of the profit‐seeking bank under the proposed two financing schemes. Our results show that the joint‐liability mechanism of the LJL financing scheme always induces the firms to overinvest in their ordering decisions (relative to the case of the individual financing scheme), which reveals that the endogenous financial terms of the LJL financing scheme have a positive effect on the firms' operational decisions. Importantly, we provide conditions under which the loan terms of the proposed two financing schemes can be properly set by the bank to make the LJL financing scheme more beneficial to the bank and the two firms, and the bank offering this financing scheme can obtain two additional benefits—that is, a higher probability of recouping all the loans and a lower profit risk (i.e., the standard derivation of the bank's random total profit), compared to individual financing scheme. The research findings provide managerial insights for a profit‐seeking bank on how to offer financial loans to capital‐constrained firms and for those capital‐constrained firms on how to cooperate with one another.

Asset securitization and bank stock price performance: Bubble increase or risk transfer?

In this study, we analyzed 40 commercial bank annual reports from 2014 to 2021 to clarify the influence of tangible and intangible asset securitization on bank stock price bubbles, based on the banks’ preference for issuing asset securitization. The empirical findings show that tangible asset securitization suppresses the emergence of bank stock price bubbles by improving internal control quality. In contrast, intangible asset securitization weakens the internal control quality while enhancing bank liquidity, exacerbating stock price bubbles. Furthermore, the results of configuration research found interactions between factors that impact bank stock price bubbles, no single factor is necessary to exacerbate bank stock price bubbles. Additionally, three configurations dominate high stock price bubbles in banks: liquidity, credit, and profit risks. The study recommends that banks develop asset securitization issuance policies, promote business transformation, prevent and resolve systemic risks, and facilitate capital market improvement and high-quality economic development.

Risk-averse two-stage stochastic programming-based closed-loop supply chain network design under uncertain demand

In recent years, there has been a growing awareness and acceptance of the concept of green environmental protection among the public, primarily due to the worsening environmental issues and increased emphasis by governments on corporate social responsibility regulations. As a result, the management of closed-loop supply chains has gained significant attention from both businesses and researchers. Most stochastic programming models addressing closed-loop supply chain (CLSC) under uncertainty are typically designed to be risk-neutral. In this paper, a risk-averse two-stage stochastic programming (RATSSP) model for the closed-loop supply chain network design (CLSCND) problem considering facility capacity level decisions under uncertain demand. It is aiming to trade off the expected total profit and the profit risk, based on a given degree of responsive risk aversion. Due to the NP-hard nature of the CLSCND problem, this paper applies simplified swarm optimization (SSO), genetic algorithm (GA), and particle swarm optimization (PSO) algorithms to solve the problem. To improve the efficiency and quality of the obtained solutions, we propose a parallel computation meta-heuristic algorithm, parallel simplified swarm optimization (PSSO), along with parallel versions of PSO and GA. Computational results show the effectiveness of our proposed model, with PSSO demonstrating the best robustness and solution quality among the considered algorithms.

Research on key influencing factors for site selection of DC microgrid-based hydrogen-electric hybrid refueling stations

In the context of the dual-carbon economy, HRSs play a critical role as an essential intermediary hub for upstream hydrogen production, midstream hydrogen storage and transportation, and downstream vehicle fueling. The use of renewable energy sources for hydrogen production and refueling has become a topic of great interest, and direct current (DC) microgrid-based HRSs are a promising model. However, there is a lack of research on the key influencing factors for the site selection of electric-hydrogen hybrid refueling stations. To address this research gap, this study reviewed the scientific literature on refueling station site selection and identified 34 site selection factors based on the characteristics of DC microgrid-based electric-hydrogen hybrid refueling stations. The importance of these factors was evaluated through a combination of fuzzy Delphi and LBWA models, and an optimized site selection evaluation index system was constructed. The results showed that hydrogen storage technology, wind speed, hydrogen production technology, lighting conditions, spatial safety, profit risk, and leakage risk are the key factors that influence site selection decisions. After eliminating nine non-important indicators, a site selection index system with 1-4-25 layers factors was established. The proposed key factors and index system have important guiding and reference significance for governments and investors in making site selection decisions and managing electric-hydrogen hybrid refueling station projects.

A comparative study on a firm’s optimal production decision considering risk aversion and carbon policies

To cope with global warming and achieve the goal of carbon emission reduction, various carbon policies have been implemented in many countries and regions. Some studies have indicated that with the popularity of low carbon, a small proportion of consumers show a green purchasing tendency. However, for firms, it is still difficult to predict the green purchase preferences of most consumers, and firms may face greater market demand uncertainty, which will bring profit risks. We assume that a firm’s decision is subject to its behavioral considerations, that is, its risk attitude. Considering the risk preferences of decision-makers and carbon emission policies, this paper addresses decision optimization in operations management. Our purpose is to analyze the optimal production decisions of risk-averse firms under carbon cap and carbon tax policies. Adopting the CVaR (conditional value-at-risk) criterion, we construct an optimization model with the constraints of carbon policies and obtain the analytic formula of optimal solutions. Then, we compare the optimal operational decisions for risk-averse firms and risk-neutral firms and further explore the impact of risk aversion on production and the parameters of carbon policy. Finally, some numerical studies are presented to analyze the carbon policies and risk aversion on firms’ operational decisions and give some managerial insights based on the analysis results.

Gestión de cartera de inversión renta variable aplicando la Teoría de Portafolios de Markowitz

Investment Portfolio Management equities is based on the investor reasoning behavior minimizing risks and maximizing profits, benefits offered by Markowitz Portfolios Theory (TPM onwards). The goal is to manage investment Portfolios equities applying TPM to determine from this one if a financial assets Portfolios negotiated in Standard y Poor's 500 (SyP 500) deals with the maximizing investor profits considering a minimal variance. The population was made by 505 enterprises composed by 11 economic sectors SyP 500 rate. Some basic analysis filters were used in order to obtain the same and 34 enterprises our of the main economical sections of SyP 500 rate were identified to which TPM was applied to investment Portfolio Management equities and financial tools such as FINVIZ, Yahoo finance, Select Sector supported by Microsoft Excel were used. The research design was pre-experimental with a quantitative-qualitative approach. One of the conclusions was that the Investment Portfolio Management equities had a 52,379% performance producing a 3,086% and 5,892% monthly expected profits risk.

A contract-based trading of power flexibility between a variable renewable energy producer and an electricity retailer

Variable renewable energy producers and electricity retailers encounter several uncertainties in their decision-making problems, such as intermittency of renewable energy sources, variability of consumption, and market price volatility. To cope with these uncertainties, this paper presents a new contract-based trading mechanism of power flexibility (FlexCon) between two parties, a variable renewable energy producer and an electricity retailer. The proposed mechanism is managed by a new entity, named FlexCon operator, to oversee the energy and financial trades through the contract and coordinate the transactions with the system operator. Through the FlexCon, the parties are able to exchange their energy imbalances as a source of power flexibility to alleviate the negative impacts of uncertainties in their decision-making problems. To this end, two two-stage stochastic linear problems are introduced from each party’s point of view. In the first stage, the variable renewable energy producer and the electricity retailer submit their bids to sell and purchase in the day-ahead market, respectively. Following the day-ahead market clearing, closer to the delivery time, the parties submit their decisions on the contract to the introduced FlexCon operator. The operator allocates possible power flexibility transactions based on the surpluses or shortages of the parties. Assuming that the imbalances are not completely resolved with the FlexCon, the remaining deviations are settled in the balancing market. The parties’ decisions related to the balancing market and the FlexCon are modeled in the second stage of the stochastic problem. The uncertainties associated with prices, renewable generation, electricity consumption, and the maximum exchangeable power flexibility through the FlexCon are considered via scenarios. Meanwhile, the profit risk is considered by the Conditional Value at Risk measure. The numerical results show that FlexCon effectively diminishes the impacts of uncertainties on the parties’ profit.

Technical Note—Optimizing Risk-Balancing Return Under Discrete Choice Models

Similar to individual investors, firms balance revenue or profit risk with the expected return on investment. A stable cash flow is required to satisfy private and public shareholders or to maintain solvency. Product prices impact both the expected demand for the products and the volatility of the demand, and consequently a firm’s revenue or profit risk. This paper presents models and results that demonstrate how risk sensitivity can inform pricing strategy. The authors show that a firm’s distaste for risk not only causes the firm to discount its products in exchange for lower profit volatility, but also reduces the firm’s incentive to price differentiate among the products. The findings also provide insight into how firms with varying degrees of risk aversion may price products of different quality and how this pricing strategy affects product market share.