Profit Maximization Research Articles

Land and technology requirements for economically prosperous smallholder farming in sub-Saharan Africa: Evidence from Tanzania

Making a living from a small farm is difficult in sub-Saharan Africa. In this paper, we quantify how difficult, using a simple, robust, relation between per capita daily income from farming (FPDI), land per capita and whole-farm net profitability per hectare. This relation allows the calculation of the land area required to generate various levels of household income as a function of farm performance. We use nationally representative household data for Tanzania to investigate the range of whole-farm profitability and to estimate an upper limit for it. For 6818 cases where households with land reported figures for gross crop and livestock revenues and for costs in any of the three years 2009, 2011 or 2013, actual median whole-farm net profitability was only $454/ha/y even without including the opportunity cost of family labour. When those were considered, median net profitability was negative $238/ha/y, i.e. a net loss. The maximum whole-farm profitability achieved was $4485/ha/y without family labour costs and $2742/ha/y with it. We evaluated actual and potential farm performance for their ability to generate a range of values of FPDI up to $10 per person per day. Most farms are not very profitable, particularly when household labour costs are considered, and few would be considered economically prosperous. Our analysis underscores the fact that improving their operations or adopting new technologies alone is unlikely to lift many smallholder farmers out of poverty in developing countries, given typical farm size distributions and reasonable assumptions about the realized economic returns to adoption of currently available agricultural technologies. While continued agricultural R&D investments are certainly worthwhile, such efforts alone will be insufficient to meaningfully address welfare needs of the world's rural poor. This suggests that agricultural development programs should expand their attention to incorporate off-farm and non-farm components of the rural economy.

Some real Life Application of Derivatives in Economics

In this assignment, we addressed the usage of derivatives in several areas of economics, such as demand elasticity, cost minimization, and profit maximization. In addition, derivatives are used to calculate marginal revenue, marginal cost, and marginal product. This work is motivated by the work of [1-24].

Optimizing power systems and microgrids: A novel multi-objective model for energy hubs with innovative algorithmic optimization

This article delves into the dynamics of power system and microgrid planning, emphasizing the emerging significance of energy hubs. The study introduces a pioneering multi-objective model that integrates economic considerations and microgrid pollution mitigation. The focus is on renewable sources such as wind and solar, coupled with advanced energy storage systems like E-fuel. Sophisticated probabilistic modeling techniques address uncertainties in renewable resources, complemented by a demand-side management program for cost reduction during peak hours. Transforming into an optimization problem, an innovative algorithm inspired by African vulture foraging behaviors provides a distinctive approach to energy landscape optimization. In a comparative analysis with established models, this approach demonstrates proficiency in simulating market behavior and providing optimal strategies for profit maximization. In a simulation analysis of four scenarios, the impact of risk assessment, a novel electronic fuel storage market, and an innovative energy storage solution on operational costs and pollution emissions is scrutinized. Notably, the proposed method excels in Case 4, showcasing a significant reduction in both operational costs and emissions. Case 4 demonstrates a substantial reduction in operational costs to $1745.732 and pollutant releases to 10753.621 kg, outperforming existing models with lower operational costs and pollutant releases.

Optimal selection of manufacturing enterprise financialization based on simulated annealing investment portfolio theory

The global market competition is becoming increasingly fierce, and manufacturing enterprises need to invest and expand. However, the traditional financial optimization of manufacturing enterprises has faced problems such as low efficiency and inaccurate search for the optimal solution, which has made manufacturing enterprises likely to face financial risks. The investment portfolio can enable enterprises to obtain the maximum profit on a certain risk level, or reduce their investment risk on a certain return level as far as possible. If the combinatorial optimization is realized, it can be applied to the optimal selection of manufacturing enterprises’ financialization. This article analyzed the respective characteristics of Genetic Algorithm (GA) and Simulated Annealing (SA) algorithms, and analyzed the combination of GA and SA algorithms to solve the optimal investment portfolio through GA-SA algorithm, thereby helping manufacturing enterprises to make the optimal choice for financialization. The experimental results of this article indicated that the GA-SA algorithm solved the problem of GA algorithm easily falling into local optima, SA algorithm’s initial temperature and generation mechanism, and improved the efficiency of finding the optimal solution. Meanwhile, the experimental results showed that the average optimal solutions of Genetic Algorithm, Simulated Annealing algorithm, and GA-SA algorithms for 36 stock portfolios in Enterprise 1 were 69, 69, and 107, respectively. The average optimal solutions of the three algorithms for 36 stock portfolios in Enterprise 2 were 73, 90, and 112, respectively. This proves that the number of optimal solutions searched by GA-SA algorithm is higher than that of GA and SA algorithm, and also proves that it is effective to use GA-SA algorithm to optimize investment portfolio and help manufacturing enterprises to make optimal financial choices.

Entrepreneurial Creative Thinking and Venture Performance: Reviewing the Influence of Psychomotor Education on the Profitability of Small and Medium Scale Firms in Port Harcourt Metropolis

The significance of small and medium enterprises to an economic development of a country cannot be overemphasized. The growth of a business depends on the development of abilities needed to execute a smooth running of day business activities. Research has established the fact that fast economic growth of regions lies on the extent of trade activities in the area. Given this established importance of enterprise, this present study aims at empirically developing the relationship between entrepreneurial creative thinking and venture performance with specific reference to small and medium scale firms in Port Harcourt metropolis. Descriptive survey design was adopted and primary data were used. The data collected were analyzed using mean, aggregate mean, and Spearman rank correlation with the aid of statistical package for social sciences, version 25. Findings shows that there is a significant and positive relationship between psychomotor education (our proxy for creative thinking) and profitability, as indicated by p-value of at 0.05 level of significance. We conclude that entrepreneurial creative thinking is an ingredient that managers of small and medium enterprises deploy to achieve maximum profit. Based on the empirical findings and conclusion, we recommend that there should be a need for policymakers to consider developing small and medium enterprises, not only through the provision of social amenities but also development of public agenda for the acknowledgement of creative thinking, skill development, and prioritization of skills improvement for both expert and non-expert business owners.

Implementation of Activity Based Costing Method in the Yellow Noodle Industry

This study aims to determine the application of the activity based costing method on yellow noodle industry. The activity based costing method is aimed at presenting accurate of cost of products for management purposes, by carefully measuring the consumption of resources in every activity used to obtain maximum profit. This study uses a qualitative model with an evaluation approach, where the interactive model used is three procedures; data reduction, data presentation, and drawing conclusions or verification. Findings, in this study there are 2 inefficient production process activities, namely the activity of the yellow noodle drying process where the allocation of labor costs uses fixed costs and the process of weighing the yellow noodles which uses the same labors as the cost per unit is different. Based on the application of the activity based costing method, the two inefficient activities are converted into variable costs per unit and allocated in the parent process activity. The impact of allocation changes is an increase in profit per unit, from Rp. 6,475 per pack of yellow noodles to Rp. 7,167 per pack of yellow noodles.

Optimal capacity configuration and dynamic pricing strategy of a shared hybrid hydrogen energy storage system for integrated energy system alliance: A bi-level programming approach

The shared energy storage system is recognized as a promising business model for the coordinated operation of integrated energy systems (IES) to improve the utilization of energy storage and the consumption of renewable energy. As the hydrogen energy gradually receives more attention, this paper constructs the structure of a hybrid hydrogen energy storage system shared by an IES alliance in a dynamic pricing mode. A bi-level optimization model for the shared hybrid hydrogen energy storage system (SHHESS) is proposed to optimize the capacity configuration decisions and the pricing strategy jointly. The upper level determines the capacity and dynamic price of SHHESS with maximum profits and the lower level obtains the optimal operation of the IES alliance minimizing the total operation costs. The proposed model is solved by an improved PSO-GA algorithm and CPLEX solver. Finally, numerical tests are conducted in different scenarios. The results show that the hybrid energy storage system improves the daily profits of SHHESS by 70.3% and 5.44%, and reduces the renewable energy curtailment by 80.93% and 48.92% respectively compared to the battery-only and hydrogen-only systems. Additionally, the daily operation cost of the IES alliance is 35.2% lower than the individual operation scenario. The proposed model confirms the feasibility and superiority of the hybrid hydrogen energy storage system in a sharing business mode.

Game theoretical analysis in two-echelon sustainable supply chains to manage and coordinate strategic decisions

Business firms and consumers are increasingly and rapidly realizing the benefits of adopting environmental responsibility. The business firms stress including it in their supply chain strategy and/or operations. This paper explores the environmental consciousness and quality attentiveness of consumers in a supply chain. Demand for the product depends on its price, eco-friendly level, and quality of the product. Three decentralized models are developed under three different game theoretical settings. A comparative study of the three game-theoretical models reveals several characteristics. It determines conditions under which channel members can decide the policy for the best possible benefit. The present work explores the effect of customer environmental awareness on the optimal decision. Production of eco-friendly items is also the prime consideration of our paper. It reveals that the manufacturer gets the most profit in the manufacturer Stackelberg game model, but the retailer gets the maximum profit from the retailer Stackelberg game model. Although channel members prefer their leading position to make the game theoretical decision-making process, the most decentralized channel profit is obtained from the Nash game model. Thus, consumers will also benefit, and the best channel profit can be obtained if the channel members agree to make decentralized decisions using the Nash game model. The centralized channel profit outperforms all three decentralized channel profits. The paper applies the concepts of sub-game perfect equilibrium and alternating offer bargaining to coordinate the channel and distribute surplus profit. Finally, analytical results are verified using numerical examples.

Comparative Economics of Different Management Tactics by Novel Insecticides against Pest Complex on Capsicum (Capsicum annuum L.) under Protected Conditions

Field experiment was conducted under shade net house at Hi-Tech Horticulture Farm, Rajasthan Agricultural Research Institute, Durgapura (Sri Karan Narendra Agriculture University, Jobner), Jaipur, Rajasthan to work out the economics and cost benefit ratio of different management strategies by three spraying of eleven bio-rationale and newer pesticides against Yellow Mite, Polyphagotarsonemus latus (Banks), thrips, Scirtothrips dorsalis Hood, aphids (Aphis gossypii Glover, Myzus persicae Sulzer), Whitefly, Bemisia tabaci (Gennadius) and Beat army worm, Spodoptera exigua (Hubner) during summer 2014 and 2015 on capsicum (Capsicum annuum L.). The result on the basis of pooled data indicated that maximum net profit of Rs 77185/ha was obtained in the treatment of fipronil 0.005% with the yield of 51.46 q/ha followed by emamectin benzoate 0.002% (Rs 67422/ha) with the yield of 49.77 q/ha. The minimum net profit of Rs 23840/ha was recorded in the treatment of NSKE 5% followed by azadirachtin 0.0003% (Rs 29876). The net profit ranging from Rs 53613/ha to Rs 60263/ha was computed in the treatment of acephate (Rs 53613/ha), spiromesifen (Rs 59971/ha), spinosad (Rs 58262/ha) and indoxacarb (Rs 60263/ha), whereas, Rs 39125/ha to 41476/ha was found in propargite and novaluron. The maximum incremental cost benefit ratio (1:20.23) was found in fipronil (0.005%) followed by 1:17.99 in the treatment of acephate (0.075%). The minimum ICBR (1:4.64) was recorded in the treatments of novaluron followed by spinosad (1:5.96). Study revealed that three spray of fipronil 5 SC @ 1 ml/l or emamectin benzoate 5 SG @ 0.4 g/l can be suggested to the farmers for the management of pest complex on capsicum under shade net house conditions during summer for off season production.

Identifying and Dealing with Interdependencies and Conflicts between Goals in Manufacturing Companies’ Sustainability Measures

Companies are increasingly focusing on sustainable business practices. Internal and external stakeholders’ expectations manifest in legal requirements, national and international standards, and market and customer expectations, among other things, must be considered. In addition to profit maximization, which is the usual target for corporate management, management must consider environmental sustainability aspects such as resource efficiency, greenhouse gas intensity, and a company’s emissions behavior. In addition, social aspects related to the company’s employees, the immediate urban environment, the situation in the supply chain, and effects on the market environment must increasingly be considered. Specifically, companies are faced with the challenge of dealing with conflicting objectives regarding the various aspects of sustainability and, if necessary, weighing them up against each other. These trade-offs must be made against the company’s socio-economic and ecological environment, corporate strategy, and sustainability goals. This paper provides an overview of current approaches and research gaps on this topic through a literature review. It highlights the lack of methods and frameworks to specifically deal with trade-offs and conflicts between goals.

Role of self-actualization in green production behavior: Evidence from rice smallholders in China

Understanding who adopts green production and why are important issues that need to be addressed in the context of increasingly severe agricultural pollution. Previous studiesh have generally researched smallholder subsistence orientation, typically employing profit maximisation or risk minimisation models. However, Chinese farmers have differentiated, and have unique characteristics. This study collected 960 random rice farmers and their village committee administrators (n=19) and conducted quantitative analysis. The findings revealed that 94.9% of the farmers’ rice-planting area was less than 2 ha, whereas 80.21% of farmers self-reported their rice production purpose as family self-feeding. Furthermore, using the new standard to define smallholders based on whether their production purpose is self-feeding or selling, non-smallholders have an overall advantage and pass the t-test. Even more non-smallholder (76.32% ) intentionally choose green pesticide than smallholders (66.1%), but their decision-making logic is different. Binary logistic regression results show that three aspects of self-actualization (environmental, market, and personal) positively and significantly affects the green production behavior of smallholders, but not significant for non-smallholders. In China, where smallholders are the mainstay of agriculture production, green production by smallholders will greatly improve the ecological environment and provide higher-quality agricultural products.

Optimal product quantity linear programming model for profit maximization in plastic small medium manufacturing firms

Planning production and maximizing profits can be difficult tasks for small and medium-sized manufacturing businesses (SMEs). Owing to their difficulties implementing the newest and most advanced Industry 4.0 technologies, small and medium-sized enterprises (SMEs) generally depend more on expert guidance. Thus this study focuses on the development of a Linear programming model for determining the optimum quantities of product in order to maximize profit profits in manufacturing Small medium enterprises. Data spanning over a period of forty five months was obtained from a manufacturing small and medium-sized enterprise. An optimization was developed in the study to determine the optimal product quantity for profit maximization. Based on the developed model and its optimization, it was determined that the optimal production quantity for the plastic factory to be 12000cups resulting in a maximum profit of N456000. This optimization approach provides valuable insights for the plastic factory’s production planning.

Optimal information disclosure in a production-inventory queueing system

This study considers a production-inventory queueing system, where customers decide whether to wait for the item or leave without a purchase if a stockout occurs. The system manager determines the joint pricing and inventory control policy. In addition, the system manager can choose whether or not to provide information about the system state to arriving customers. Our strategic production-inventory queueing system includes the observable, unobservable, and almost unobservable systems, which are obtained by appropriately choosing the information disclosure policy by the system manager. In this study, we find the optimal information disclosure policy, as well as the optimal price and the optimal inventory control policy for the profit maximization and social welfare maximization. Under the optimal policy, the system manager should disclose the system state if and only if the queue length exceeds a certain threshold.

Environmental, social, and governance performance as an influencing factor of financial sustainability: Evidence from the global high‐tech sector

AbstractThe corporate sector strives to improve its environmental, social, and governance (ESG) performance to transition from short‐term to sustainable long‐term profit maximisation. This study thus explores the impact of ESG performance on the financial sustainability (FS) of a sample of the top 100 global high‐tech firms. Specifically, we employ the two‐step generalised method of moments to control for endogeneity bias and a panel data fixed effects model to control for unobserved heterogeneity. Empirical findings reveal that overall ESG performance has a statistically negative association with the FS of global high‐tech firms. Individual pillar‐wise analysis reveals that the environmental and social (governance) pillar has a negative (positive) association with the FS of the sampled firms. This result proves that each ESG pillar exerts varying effects on corporate performance indicators. Overall, the results provide empirical evidence that could help policymakers devise policies for investing optimally in ESG indicators to spur corporate FS.

Metaheuristic optimization algorithms comparison adopted for the profit maximization of electricity market participants

The electricity market faces numerous challenges due to the growing demand for energy, increasing penetration of renewable energy sources, and the need for grid reliability and efficiency. To address these challenges, optimization algorithms have emerged as essential tools for optimizing various aspects of the electricity market, including generation, transmission, distribution, and demand-side management. The review can be done by providing an overview of the key components and challenges of the electricity market, including generation dispatch, unit commitment, economic dispatch, transmission network optimization, and demand response management. It then systematically examines a wide range of optimization techniques employed in addressing these challenges, including linear programming, mixed-integer linear programming, nonlinear programming, dynamic programming, genetic algorithms, particle swarm optimization, simulated annealing, and machine learning-based approaches. This paper presents a comparison of optimization algorithms, RCEDUMDA (Ring-Cellular Encode-Decode Univariate Marginal Distribution Algorithm) and CL_HC2RCEDUMDA (Hill Climbing to Ring Cellular Encode-Decode Univariate Marginal Distribution Algorithm) for the profit maximization of Electricity Market consumers & prosumers.

Optimal format design in green tourism supply chain in the presence of a dominant online travel agency

Due to a large consumer base owned by a dominant online travel agency(OTA), green hotels widely cooperate with the OTA to sell their products. This study develops a green tourism supply chain model involving an OTA and a green hotel. The study aims to provide valuable insights for the OTA and hotel in optimizing their decision-making process when they come to reach an agreement on cooperation formats among price-only, cost sharing, and revenue sharing. The findings indicate that cost sharing and revenue sharing formats are more effective than price-only format in incentivizing the hotel to improve its environmental efforts. Moreover, these two formats result in higher wholesale prices determined by the hotel compared to the wholesale price set in price-only format. This study also recommends the revenue sharing format as an optimal format, which could lead to a win-win outcome for both the OTA and hotel, achieving profit maximization under specific conditions. Overall, by effectively implementing cooperation formats, the OTA and hotel can work together to promote green tourism supply chain performances.

Optimizing Concrete Paver Block Production: A Linear Programming Approach for Enhanced Profitability in the Construction Industry

As an operational optimization (maximization or minimization) methodology, linear programming (L.P.) in operation research has proven successful in several areas by offering logical outcomes to challenging issues, including resource constraints. The study aimed to bridge the gap between theoretical applications of L.P. and the practical needs of the construction industry, specifically focusing on determining the optimal production quantities of 60 mm and 40 mm concrete paver blocks for Janta Udhog Pvt. Ltd. as a case study to achieve maximum profitability, offering essential new insights into how L.P. may successfully handle the complex problems encountered by businesses in this industry. An interview with the owner of Janta Udhog Pvt. Ltd. was conducted to obtain the primary data for the study. Secondary data such as sale records, monthly demand of each product, and inventory records were also obtained to formulate a linear programming model. The model was then solved using the LINGO software. This research underscores the optimal production recommendations for Janta Udhog Pvt. Ltd., advising the manufacture of 566.67 units of the 60 mm block and 350 units of the 40 mm block, leading to a maximum daily profit of NPR 2966.67. By applying linear programming techniques, these findings contribute to a more informed and strategic decision-making approach in the construction sector. The study illuminates the benefits of utilizing linear programming in challenging situations, providing valuable insights for academics, business owners, and decision-makers.

The Big Bank Scam: Failure of Corporate Governance

The case deliberates the series of events exposing serious shortcomings in corporate governance and risk management practices of one of India’s oldest and most venerable financial institutions but also cast a glaring spotlight on various unfathomable issues of corporate governance such as weak institutionalisation of whistleblowing mechanism, ethical lapses and regulatory oversight within the banking sector. The case provides an opportunity to understand the key components of corporate governance structure and consequences of poor corporate governance. The case highlights the responsibility of the board of directors and audit committee and discusses the changes required in the corporate governance structure necessary to ensure that such incidents do not take place. The case attempts to unearth the weaknesses in the bank’s internal processes that led to a scam of this magnitude and why it remained ongoing and undetected for several years. We found that there is a need for banks to leverage the latest advancements in technology to upgrade their internal functions and processes and make them more accountable and transparent. Further, it also opens the debate on whether public sector banks and other financial institutions should be guided solely by the profit maximisation motive, or they also meet their social obligations.

Responding to consumer environmental awareness: A variational inequality approach to green manufacturing optimization

In response to increasing consumer environmental awareness, our study introduces a sustainable supply chain optimization model that stimulates competition among multiple green manufacturers within an uncertain market context. Each manufacturer crafts a selection of products showcasing various degrees of greenness, purposefully designed to meet the expanding demand of environmentally conscious consumers. This strategic model emphasizes profit maximization for green manufacturers, necessitating the definition of ideal greenness levels and production quantities for an array of product types. By employing variational inequality theory, we transmute the preliminary optimization model into an interconnected variational inequality problem. We propose an improved Euler algorithm, a proficient tool for attaining equilibrium solutions. Empirical scenarios inspired by the electric vehicle industry lend credibility to our model, indicating that the surge in consumer environmental awareness compels manufacturers to diversify their offerings and accentuate their products’ greenness levels. Intriguingly, the research suggests that escalating competition can incentivize manufacturers to elevate their products’ greenness levels, strategically countering potential profit erosion. In addition, the study reveals that intensifying consumers’ green utility sensitivity doesn’t invariably augment demand for manufacturers, even with significant improvements in product greenness. This paradox highlights the necessity for manufacturers to strategically adjust their production approaches in light of varying consumer preferences. Moreover, when the level of consumer environmental awareness achieves a certain level, the fierce competition might not always be harmful to some manufacturers and the industry if they can adopt effective strategies to improve green utility sensitivity.

Research on pricing strategy of dual-channel supply chain based on blockchain technology under carbon trading

In the context of the dual-carbon goal, it is of great significance to study the application of blockchain technology in the dual-channel supply chain under the carbon trading mechanism for the carbon emission reduction of enterprises and the overall profit maximization of the supply chain.In this paper, two decision models of the supply chain under secondary carbon trading are constructed to analyze the two cases of whether to adopt blockchain technology. Stackelberg model is used to study the impact of blockchain technology on the pricing decision of the dual-channel supply chain under carbon trading, and the two models are compared and analyzed.According to the research results, after the application of blockchain technology, wholesale prices, direct sales prices, retail prices, and profits of retailers and manufacturers have increased compared with the non-use of blockchain technology, which is conducive to promoting the development of carbon emission reduction for manufacturers.