Profit Maximization Research Articles

Modeling an on-demand meal delivery system with human couriers and autonomous vehicles in a spatial market

This paper investigates the impacts of introducing autonomous vehicles (AVs) into an on-demand meal delivery system at a strategic level. The proposed model consists of (i) a microscopic physical model describing the delivery process for bundled orders and (ii) a macroscopic network equilibrium model characterizing the interactions among customers, human couriers (HCs), and AVs, as well as couriers’ repositioning behaviors in the market. A tailored algorithm based on the Alternating Direction Method of Multiplier (ADMM) is developed to solve the platform’s optimal pricing and maximize its profit. To investigate the impact of AV operations, we test three AV distribution rules, i.e., distributing AVs evenly in the space (Rule 0), proportional to demand (Rule 1), and inversely proportional to demand (Rule 2). The numerical experiments show that Rule 2 archives the maximum platform profit, along with the highest service throughput and the hourly earning rate of HCs. Nevertheless, the numerical experiments adopting the parameters calibrated by current market conditions show that the employment of AVs does not show significant benefits to the platform or other stakeholders. It can only generate a higher platform profit when the AV operation cost is lower than HCs’ hourly earnings in a purely labor-based MDS system. As the AV fleet size expands, the improvement of service quality is rather minor meanwhile the hourly earning of HCs drops substantially.

Design and Implementation of an Efficient Franchise Management System: Enhancing Operational Consistency and Growth

Abstract–The Franchisee Web Portal project aims to revolutionize the management and communication processes within franchise networks. Franchise businesses often face challenges in maintaining efficient communication channels and managing operations across multiple locations. This project addresses these challenges by developing a centralized web portal tailored specifically for franchisees.The portal offers a range of features designed to streamline operations and enhance communication among franchisees, franchisers, and other stakeholders.The portal provides a centralized platform for franchisees to communicate with each other and with the franchiser. This fosters collaboration, knowledge sharing, and problem-solving among franchisees, leading to improved operational efficiency and consistency across the network.Overall,the Franchisee Web Portal project represents a significant step forward in modernizing franchise operations and fostering collaboration and communication within franchise networks. By leveraging technology to create a centralized platform tailored to the needs of franchisees, the portal helps drive operational excellence and ensure the long-term success of franchise businesses.The portal features robust reporting and analysis capabilities, allowing franchisees to track key performance metrics, identify trends, and generate insights into their operations. This empowers franchisees to make informed decisions and optimize their businesses for maximum efficiency and profitability. Keywords – Operation Management, Inventory Management, Franchisee Network, Operational Excellence, Knowledge Sharing.

Empirical Study to Evaluate Financial Fitness of Listed Commercial Banks of Pakistan

The main purpose of this research is to find the effect of financial fraud, bank size, liquidity, solvency, and efficiency on the financial performance of selected Pakistani commercial banking sector. This research is conducted for assessing the financial stability of the commercial Banking sector of Pakistan. In this research, the ratio analysis technique is adopted for investigating the financial performance of the Banking Sector for the period 2012 to 2018. This study found that bank size, financial fraud, efficiency, solvency and liquidity have a significant impact on the financial performance of commercial banks in Pakistan. This research suggested that commercial banking zone working in Pakistan should be brought into being place fraud discernment appliance by framing up a well-organized and systematic, well-established, and reliable and operating fraud detection sub-division to supervise all the transactions that are contemplated vulnerable to fraudulent practices to minimization vice for them to maximization of profits for better monetary/financial progress/performance.

The Impact of Corporate Social Responsibility on Financial Performance: A Comparative Study of Green and Non-Green Firms

This research compares green and non-green companies to investigate how corporate social responsibility (CSR) affects financial performance (FP). Although the relationship between CSR and FP has been studied in the past, the findings have been contradictory, and the conclusions can’t be reached with certainty because there isn’t enough specific data on CSR. The main goals of this study are to examine the relationship between corporate social responsibility (CSR) and financial success, as well as the possible effects of increasing media attention on CSR initiatives on business outcomes. The study intends to address important concerns about the advantages and results of CSR participation while acknowledging the variety of stakeholders engaged in assessing the business value of organizations. The study looks at the kinds of CSR activities that provide positive CSR effects and assesses whether CSR initiatives add to or subtract from profit maximization objectives. The study advances our knowledge of how corporate social responsibility (CSR) affects financial performance, especially when it comes to green versus non-green businesses. Keywords: Corporate social responsibility, financial performance, comparative study, green firms, non-green firms, stakeholders

Designing Risk Mitigation Strategies for Agricultural Supply Chain: A Supply Chain Finance-Based Approach

Abstract The agricultural supply chain is distinguished from the manufacturing and service supply chains by its complexity and length. These characteristics emphasize the importance of risk management measures for this supply chain, which will increase farmer income, market stability, and food security. This research aims to design risk mitigation strategies, especially demand risk, in the rice farming supply chain in Tana Paser District, Paser Regency, East Kalimantan. Monte Carlo simulation was utilized to predict the average rice demand and conduct sensitivity analysis. Three financial scheme strategies were compared: soft tolling, hard tolling, and contract farming, to assess the best strategy that provides maximum profits for agricultural supply chain actors. From the simulation results, the average predicted value for rice demand was 2.78 tonnes. The optimal quantities of q1 (processed material), q2 (raw material), and q3 (seeds) obtained from sensitivity analysis were 2.2 tons, 2 tons, and 2 tons, respectively. The soft tolling strategy provides maximum profits for all agricultural supply chain players, with a total profit of IDR 17,471,000.00, considering that implementing this strategy involves all supply chain stakeholders in determining the contract decision (q).

Integrated Shipment Consolidation and Vehicle Routing Problem (VRP) for Profit Maximization in E-commerce Supply Chains with Dynamic Demand

Integrated Shipment Consolidation and Vehicle Routing Problem (VRP) for Profit Maximization in E-commerce Supply Chains with Dynamic Demand

Is it possible to reconcile the economic and social objectives of companies? A critical perspective

Purpose This paper aims to examine whether reconciling profit maximization and social welfare as two possible aspirations of company is feasible. Design/methodology/approach The possible corporate goals are presented by drawing an arc from purely profit-maximizing organizations via a combination of profit and social objectives to organizations clearly serving social utility. In addition to this sorting principle, the order of the different positions presented also takes into account the number of goals and goal-setters. Findings The primary finding of the study is that none of the business concepts discussed here met the initial expectations as for economic and social objectives. The study points to the need to redefine the purpose of business within a broader social science framework. Research limitations/implications For a critical perspective, this paper considers only those standpoints that emphasize a certain form of social utility beyond profitability resulting from business activity directly or indirectly. Originality/value In addition to revealing the relationship between the two aspirations, the novelty of the paper lies in the attempt to explore through normative critique and empirical evidence the validity of the expectations regarding the goals.

Research on Vertical Cooperation and Pricing Strategy of Electric Vehicle Supply Chain

To determine a vertical cooperation strategy and address the optimal pricing problem of the electric vehicle (EV) supply chain, a supply chain system consisting of two competing EV manufacturers (M1 and M2) and a battery supplier is studied. Firstly, three cooperation strategy models were constructed for the battery supplier and the EV manufacturers, namely: Strategy N (neither the battery supplier nor the two manufacturers cooperate with each other); Strategy I (M1 cooperates with the battery supplier); and Strategy II (M2 cooperates with the battery supplier). Then, the Stackelberg solution method was used to obtain the optimal equilibrium decisions under the three strategic models. Finally, the effect of the preference coefficient of consumers for leasing EVs per unit on the optimal equilibrium decision was analyzed. We found that: (1) The wholesale price of batteries provided by the battery supplier to M1 is always greater than to M2. (2) Strategies I and II prompt M1 and M2 to reduce the unit and fixed rental prices of EVs to some extent, while intensifying the competition between the two manufacturers in terms of EV lease prices. (3) When the consumer preference coefficient (θ) for leasing EVs per unit provided by manufacturer M1 is relatively small, the cooperation alliance S2 and the supply chain achieve the maximum profit under Strategy II; however, while θ is large, M1, cooperative alliance S1, and the entire supply chain could benefit the most under Strategy I.

Green supply chain finance model in logistics and transportation industry: improving from policies and regulation and financial digitalisation practices

ABSTRACT This study contributes to the green supply chain finance model to facilitate the alignment between financial prosperity and the green transition in the logistics and transportation industry in Vietnam. Green supply chain finance has received increasing attention of stricter environmental regulations and increases consumer demand in industries involved. This complex issue requires ongoing attention and resolution in the industry. This study aims to construct a green supply chain finance model and identify the attributes. This study employs a hybrid fuzzy Delphi and fuzzy decision-making trial and evaluation laboratory. The model is shown to be robust according to sensitivity analysis. The results show that the validated model is built by 13 criteria within five aspects. The aspects are policies, regulations, financial digitalisation approaches, and collaborative financing decision-making. The practical causal criteria include (1) shared profit maximisation, (2) government rewards, (3) sustainability agreements and to provide guidelines for the practices.

Incorporate robust optimization and demand defense for optimal planning of shared rental energy storage in multi-user industrial park

The increasing uncertainty and volatility of net load caused by the high penetration of renewable energy leads to higher demand tariffs for industrial park and potentially impacts their economic benefits. To tackle these issues, this paper develops a novel business mode to enable rental energy storage sharing among multiple users within an industrial park, and propose a robust optimization and demand defense-based iterative bi-layer planning framework. The upper layer focuses on the maximization of the investment profitability of shared rental energy storage by developing a robust information gap decision theory optimization. Meanwhile, the lower layer is dedicated to enhancing the demand defense ability of shared rental energy storage in real-time operation through the formulation of a distributed model predictive control. After that, the synchronous alternating direction multiplier method with consistency theory is derived for solving the distributed optimization. Numerical results demonstrate that the proposed shared rental energy storage is 6.391% and 7.714% more economical than shared and self-built energy storage, respectively. Moreover, the iterative bi-layer planning enables flexible energy storage capacity configuration, reduces the impact of net load uncertainty, improves the ability of demand defense, and enhances the system’s overall economy.

Сбыт металлов платиновой группы: планирование и оптимизация

Introduction. The development of methodological issues of optimizing the activities of mining and metallurgical companies and the sale of platinum group metals are highly relevant in the current market conditions due to sanctions restrictions and the severance of international economic ties. Theoretical analysis. The concept of an optimization model is formulated, the main goals for the sales unit of a mining and metallurgical company are determined, a balanced approach to monthly planning is justified, which involves dividing the sales volume into two parts: under long-term contracts and on the spot market, and the stages of constructing an optimization sales model are developed. Empirical analysis. An optimization model is presented for calculating sales volumes of platinum, palladium and rhodium within two months to obtain maximum operating profit. The model is based on regression modeling of prices for platinum group metals, a cost model built on open data from a Russian mining and metallurgical company. Results. Approbation of the methodology made it possible to justify the sales volumes of platinum group metals in two forecast periods depending on the price environment, which provide the opportunity to increase the total profit of the company under given restrictions.

Regime‐dependent commodity price dynamics: A predictive analysis

AbstractWe develop an econometric modelling framework to forecast commodity prices taking into account potentially different dynamics and linkages existing at different states of the world and using different performance measures to validate the predictions. We assess the extent to which the quality of the forecasts can be improved by entertaining different regime‐dependent threshold models considering different threshold variables. We evaluate prediction quality using both loss minimization and profit maximization measures based on directional accuracy, directional value, the ability to predict turning points, and the returns implied by a simple trading strategy. Our analysis provides overwhelming evidence that allowing for regime‐dependent dynamics leads to improvements in predictive ability for the Goldman Sachs Commodity Index, as well as for its five sub‐indices (energy, industrial metals, precious metals, agriculture, and livestock). Our results suggest the existence of a trade‐off between predictive ability based on loss and profit measures, which implies that the particular aim of the prediction exercise carried out plays a very important role in terms of defining which set of models is the best to use.

Optimizing Cloud Broker Profitability through Advanced Cloud Computing Techniques

Cloud computing has gained significant traction as an efficient solution for delivering on-demand computing resources and services. For cloud service providers, ensuring profitability while maintaining service quality is crucial. However, the prevalent single long-term renting approach often results in compromised service quality and substantial resource wastage. To address this, our paper proposes a pioneering double resource renting scheme that integrates short-term and long-term renting. This innovative approach not only guarantees optimal service quality for all requests but also significantly minimizes resource wastage. We adopt an M/M/m+D queuing model to analyse the performance indicators affecting the profitability of our double renting scheme, including the average charge and the ratio of requests necessitating temporary servers. By formulating a profit maximization problem tailored to the double renting scheme, we derive an optimized cloud platform configuration. Comparative calculations between our proposed scheme and the traditional single renting scheme demonstrate that our approach not only ensures superior service quality for all requests but also yields increased profitability. Key Words- Cloud computing, Double resource renting, Service quality, M/M/m+D queuing model, Performance indicators, Profit maximization, Short-term renting, Long-term renting.

Farming with a mission: the case of nonprofit farms

AbstractOrganizations interested in food alterity, security, and justice are often governed as 501(c)(3) nonprofits. As such, they are required to fulfill missions beyond profit maximization. This study focuses on the role of nonprofits in the agrifood system. Looking at nonprofit farms as both farms and as nonprofits, we seek to understand whether nonprofit organizations, as an alternative mode of governance, creates the possibility of an alternative economic practice, set apart from the conventional food system. We constructed a national database of nonprofit farms and the characteristics of the counties in which they are located. Our findings indicate that nonprofit farms tend not to be in the places with the most need of the services provided, which we argue is due to the structure of nonprofit governance, namely that nonprofits, while not profit-maximizing, are dependent on external resources, particularly donations. While they do operate as an alternative economic practice, their nonprofit mode of governance renders them unable to repair the failures of the current food system. Nevertheless, these farms do contribute to their local communities, both in terms of meeting their mission and as members of a broader local food system infrastructure. This is true whether or not these farms specifically state that food system transformation is part of their mission.

How price and non-price factors influence the market price of major carp: Findings from the dynamic ARDL approach

Recently, fish prices in Bangladesh have been growing, particularly the market price of major carp, even though the factors that may be contributing to this trend are unexplored. Therefore, this study considers some price and non-price factors to explore the market price dynamics of major carp species in Bangladesh. To explore the factors impacting the market price of carp fish, we apply advanced time-series econometric modeling, such as the recently devised dynamic simulated autoregressive distributed lag (ARDL) model using publicly available data on fish prices from 2005 M1 to 2021 M12. This period is attributed to the rapid transformation from mostly low-intensity farming to commercialization due to a rise in productivity and market price. Among the price factors, the findings demonstrate that the price of corn, soybean, and oilcake, and fisheries wage rate have a positive significant impact on fish price in both the short and long term. In addition, among the non-price drivers, GDP per capita, inflation rate, and fish consumption all have a significant positive influence on fish prices in the long run, whereas total production has a detrimental effect on fish prices in the long run. These results have significant policy ramifications for attaining the fish farmers' profit maximization and consumers' welfare maximization goals.

Optimization Model of Clothing Production Plan using Branch and Bound Method

The increasing number of clothing activities in Indonesia has resulted in companies having to increase their marketing and production activities in order to obtain maximum profit. One of the factors influencing the growth of basic clothing is the price of the middle class in Indonesia. This can be a strong foundation for a long-term clothing consumer base. One of the businesses engaged in the production of clothing is a garment production business. The problem that is often faced by companies is limited resources such as raw materials, capital, time, etc. Production planning is a process to produce goods in a certain period in accordance with those predicted through the organization of resources. Therefore, production optimization is one way to optimize profit and apparel production. This study aims to apply the Integer Linear Programming model and is completed using the Branch and Bound method to obtain the optimal number of clothing production in order to obtain maximum profit. The conclusion obtained from the research is the application of the Branch and Bound method to the problem of optimizing production planning at PT. GM Tactical to obtain more optimal results compared to the actual production carried out by the company.

Stock Hedging Using Strangle Strategy on Vanilla Options and Capped Options

The financial market often experiences unexpected fluctuations that can impact stock values. Therefore, investors require hedging strategies to protect their investment values from unwanted price fluctuations. This study compares the hedging results using the strangle strategy on Vanilla options and Capped options on Micron Technology, Inc. (MU) stock. The methods used are Monte Carlo simulation and Black Scholes Merton to calculate the option prices. The research results indicate that the strangle strategy on Vanilla options has unlimited maximum profit potential, whereas on Capped options, the profit is capped above. However, the potential maximum loss on Capped options is lower than that on Vanilla options. Therefore, Capped options are preferred for hedging the MU stock. The research yields significant practical and theoretical benefits. Practically, it offers investors insights into more effective hedging choices for risk management and profit potential in the stock market. Opting for capped options allows investors to control risk better while preserving profit potential. Theoretically, the study enhances our understanding of cost efficiency and risk profiles across various options strategies, making a vital contribution to financial literature.

Bioeconomics of juvenile seahorse (Hippocampus erectus) culture: Optimal harvest time

AbstractThe culture of seahorses Hippocampus erectus in captivity represents a window of opportunity for the diversification of the aquaculture activity in the ornamental industry. In this study, we have constructed a bioeconomic model to evaluate the optimal harvest time (OHT) over a culture period of 562 days. The bioeconomic model was integrated with three submodels: biological, technological, and economic. Three different mortality rates were used for different periods in culture, registering a higher survival in the period from 0 to 60 days with a rate of 53.4%. The sensitivity analysis showed that the mortality rate in this period was the parameter with the greatest influence on the benefits. The Von Bertalanffy growth model was indicated to describe the growth of H. erectus given its statistical significance using Theil's inequality coefficient, registering parameters of (L∞ = 141.62 mm) and (k = 0.0049 month‐1). The bioeconomic model determined the OHT in the 4th month of culture, the time when the maximum profit is recorded. It is concluded that the culture presents challenges to be addressed although the bioeconomic model allows for demonstrating the OHT.

A Decision Model for Pricing and Replenishment of Vegetable Products Based on Lagrangian Function Optimization

In the era of big data, superstores usually replenish and price their products based on the historical sales and demand of each item. Based on data mining, this paper analyzes the correlation between different categories using a gray correlation analysis model, then fits the relationship between total sales and cost-plus pricing for each vegetable category, and uses a time series forecasting model to predict the wholesale price and sales volume of six types of vegetables in the week of July 1st to 7th. By establishing a Lagrangian function-based optimization model with the objective function of maximizing the profit of the superstore, the total daily replenishment of each category and the cost-plus pricing as the decision variables, and traversing the solution with a step size of 0.5 sales, the total daily replenishment and the pricing strategy for the next seven days can be formulated, and the total return of the superstore in the coming week is found to be 2264.41 yuan. The optimization model based on profit maximization of superstores used in this paper provides reliable theoretical support and practical guidance for merchants to predict market conditions and plan future replenishment and pricing strategies.

Vegetable Product Pricing Replenishment Strategy Based on WOA

In fresh food superstores, the freshness date of general vegetable commodities tends to be relatively short, and the quality of vegetable commodities will deteriorate with the delay of the sales time. Therefore, how to allow supermarkets to ensure that the daily replenishment of the amount of market demand for various types of vegetable products while trying to meet the premise of maximizing their profits has become an urgent problem, this study aims to propose an innovative vegetable product prediction model based on big data, which adopts the SARIMA model to accurately predict the daily replenishment amount of each type of vegetable product in supermarkets. Meanwhile, based on the replenishment amount, the WOA model takes the addition coefficient and sales of different vegetable products as the dependent variable, and the final profit as the independent variable. The corresponding pricing strategy is formulated to maximize the profitability of the supermarket. Through solving the model, it is found that the maximum profit of the supermarket's vegetable products in the next week is 3,649.65 yuan.