Supply chain management constitutes one of the most critical and strategically consequential functions of modern retail business operations, encompassing the complete lifecycle of a product from procurement and production through warehousing, distribution, and final delivery to the end customer. In an era of growing market complexity, rapidly shifting consumer expectations, and increasing competitive pressure on profit margins, the ability to extract timely and accurate intelligence from supply chain transactional data has emerged as a defining competitive advantage for retail organizations. This paper presents a comprehensive supply chain analytics study applied to the widely used Sample Superstore dataset, a multi-dimensional transactional dataset representing four years of retail operations across the United States. The study implements an end-to-end data analytics pipeline encompassing raw data ingestion, systematic preprocessing and feature engineering using Python and its scientific ecosystem — including Pandas, NumPy, Matplotlib, and Seaborn — followed by in-depth exploratory data analysis (EDA) and the development of an interactive, multi-page business intelligence dashboard built using Microsoft Power BI. The preprocessing phase engineers five derived analytical features: Delivery Duration, Profit Margin Percentage, Discount Band, Order Year, and Order Month, significantly enriching the dataset’s analytical depth. The EDA reveals several critical findings: a strong and consistent negative correlation (r ≈ −0.22) between discount rate and profit margin that intensifies at discount levels above 40%; stark category-level profitability divergence with Technology generating approximately 17.4% profit margin versus Furniture at only 2.5%; significant regional profitability disparities with the West and East regions outperforming the Central and South; an on-time delivery rate of 81.75% indicating logistics execution gaps; and a 99.37% customer repeat rate indicating strong customer loyalty. The Power BI dashboard translates these findings into sixteen Key Performance Indicators (KPIs) across four pages covering sales performance, profitability analysis, customer behaviour, and logistics operations. Six actionable business recommendations are derived, including the implementation of a 20% discount cap policy, restructuring the Furniture category strategy, adopting a regionally differentiated discount framework, and targeting a 95% on-time delivery rate. The project demonstrates the transformative potential of applied supply chain analytics and establishes a reproducible, scalable framework that organizations can adapt to their own operational datasets.

There are livestock species such as rabbit, guinea fowl, and grasscutter in Sub-Saharan Africa which are traditionally consumed but have not received as much attention and support from policy and research compared to conventional livestock species such as cattle, sheep, goat, pig and poultry. Despite the growing interest in such neglected livestock species (NLS), evidence on their integration, production, and drivers of adoption remain sparse. This comparative study investigates the production characteristics, profitability, and determinants of farmers' choices between conventional and NLS production in Ogun and Oyo States, Nigeria. We conducted a quantitative survey of 183 smallholder livestock producers, selected using simple random and snowball sampling procedures across Ogun and Oyo States. Data were collected through questionnaires and analysed using descriptive statistics, logistic regression, and cost-benefit analysis. The findings show that women were disproportionately engaged in NLS production. Intensive and semi-intensive production systems were the most prevalent, driven by land scarcity and the adaptability of NLS to confined production environments. Feed emerged as the dominant cost component across both species, significantly impacting profitability. Logistic regression analysis showed that the choice of NLS production was positively and significantly associated with mode of land acquisition, profit, and access to credit. Profitability analysis revealed that NLS systems achieved a higher return on investment than conventional systems, offering a viable pathway for enhancing income, food security, and resilience among smallholders in the study areas. Conclusively, with an appropriate policy framework, neglected livestock species could contribute to a transformative shift in Southwestern Nigeria's livestock landscape.

This dataset covers U.S. supermarket retail sales across multiple product categories. It includes customer demographics, order details, product types, shipping methods, payment modes, and financials — revenue, quantity, and profit. The data is useful for spotting patterns: which products are actually profitable, which regions underperform, how shipping choices affect margins, and whether payment method has any real bearing on sales. Retail managers, supply chain analysts, and business strategists are the likely audience, though anyone doing retail analytics will find something here.Keywords: Supermarket Sales, Retail Analytics, Profit Analysis, Regional Performance, Data Visualization

The study examines the inter-relationship between cost, profitability and market valuation with the help of the ARIMA time series model. The study aims to understand the relationship between the cost components and profitability and between profitability and market valuation of a firm. The research seeks to understand the cost, profitability and its effect on the market valuation. The secondary data is obtained from the financial reports from the public domain for the period (2016-2025). Return on Equity (ROE), Return on Assets (ROA) and Net Profit Margin (NPM) are the measures of profitability. The share performance measurements chosen are share price, Earnings Per Share (EPS) and Price-Earnings (P/E) ratio. Trend analysis, correlation analysis and ARIMA modelling are used to detect trends and inter-relationships. The findings reveal that the total salaries and wages, finance costs and depreciation negatively affect profitability, whereas some operating expenses positively affect revenue. Further, profitability has a significant positive impact on market valuation, indicating that profitability boosts investor confidence. The findings indicate that cost efficiency leads to better profitability and hence a better market valuation. Profitability is a link between financial efficiency and market valuation.

griculture is an essential sector that significantly influences the economy and the livelihood of millions of farmers. However, modern farming is affected by several challenges such as unpredictable weather conditions, fluctuating market prices, improper crop selection, and lack of effective advisory systems. These issues often lead to reduced productivity and financial instability for farmers. To address these challenges, this paper presents AgriMitra, a smart crop recommendation system that supports farmers in making informed and profitable decisions. The system gathers data from multiple sources including real-time weather information, soil characteristics, historical crop data, farmer inputs, and market trends obtained from platforms such as Agmarknet and weather APIs. The collected data is processed and refined to ensure consistency and reliability for further analysis. Machine learning techniques such as Random Forest and XGBoost are applied to recommend crops based on environmental conditions and farmer requirements. These models consider various factors including soil suitability, climate conditions, available budget, and expected market demand. In addition, time-series forecasting models such as ARIMA and Prophet are used to estimate future crop prices and demand patterns, enabling farmers to plan their cultivation strategies more effectively. The system also includes a cultivation plan generator that provides step-by-step guidance for different farming activities such as sowing, irrigation, fertilization, and harvesting. This ensures continuous support throughout the entire farming cycle. Moreover, a multilingual chatbot with both text and voice interaction is integrated into the system to assist farmers, answer their queries, and improve accessibility. An interactive dashboard is designed to present important insights such as crop recommendations, profitability analysis, risk evaluation, and market trends. The system also provides alerts and notifications to help farmers respond to potential risks related to weather conditions, pest attacks, and price fluctuations.

Introduction Non-timber forest products such as bush mango ( Irvingia gabonensis ) are critical to rural economies in West Africa, yet their harvesting remains poorly understood in terms of economic returns and sustainability. Methods This study assessed the harvesting and economic potential of I. gabonensis in Edo State, Nigeria, using a purposive survey of 79 harvesters. Data were analysed through descriptive statistics, correlation, and regression, complemented with thematic analysis of qualitative responses. Results The results showed that harvesting is predominantly male-driven (68%), with a mean respondent age of 41 years, an average household size of 6, and a mean harvesting experience of 11 years. The activity was seasonal, occurring mainly from June to September, with an average weekly harvest volume of 124 kg per household. Regression analysis indicated that household size (β = 0.28, p < 0.05), years of experience (β = 0.32, p < 0.01), and access to productive trees (β = 0.41, p < 0.01) were significant predictors of profitability (R² = 0.47). Profitability analysis indicated that on average, each household earned a gross margin of 1 ₦103,800 (USD 71.5) per season, corresponding to a rate of return on investment of 91%. Constraints included limited access to trees (63%), declining yields (56%), and overdependence on wild stocks (72%). Discussion These findings highlight that sustainable harvesting and domestication of I. gabonensis can serve as Nature-Based Solutions (NbS), enhancing ecosystem services and promoting climate-resilient livelihoods in forest-dependent communities. The study concludes that I. gabonensis harvesting is economically viable but ecologically vulnerable, and that it requires domestication, sustainable practices, and improved access rights to secure its future contribution to rural incomes.

ABSTRACT Profitability analysis is one of the most important tools used to measure the financial strength, operating efficiency, and long-term sustainability of any business organization. In the highly competitive automobile industry, profitability determines the ability of a company to survive market fluctuations, changing consumer preferences, rising raw material costs, and technological transformation. Maruti Suzuki India Limited has established itself as one of the leading passenger vehicle manufacturers in India through strong brand value, wide product portfolio, extensive dealer network, cost efficiency, and customer trust. Various accounting ratios, income statement trends, operational performance indicators, and the company's market position are the primary focus of this study. The analysis aids in comprehending the company's efficient resource utilization for profit and shareholder value. The study also examines the relationship between sales growth, production efficiency, operating margin, net profit margin, return on assets, and return on equity of the company over a period of years. It highlights the impact of economic conditions, fuel prices, inflation, taxation policies, and consumer demand on company profitability. The findings reveal that Maruti Suzuki India Limited has maintained a strong market presence through innovation, fuel-efficient vehicles, strategic pricing, and effective cost control measures. The business has demonstrated resilience and consistent financial performance despite obstacles like competition, shortages of semiconductors, and shifting environmental regulations. Investors, researchers, management students, and policymakers can all benefit from this study's understanding of automotive sector profitability trends. Keywords: Profitability Analysis, Automobile Industry, Net Profit, Operating Margin, Return on Equity, Financial Performance, Maruti Suzuki.

Because fixed costs such as capital investment, lease-related expenses, and depreciation vary substantially according to institutional case volume, timing of platform introduction, and local accounting policy, direct cross-platform comparison based on total cost may be difficult to interpret in routine practice. This study aimed to descriptively compare marginal profit rates of conventional laparoscopy (Lap), the da Vinci single-port (SP) system, and the da Vinci multi-port platforms in colorectal cancer surgery using institutionally standardized running costs. We retrospectively reviewed patients with resectable primary colorectal cancer who underwent minimally invasive surgery at our institution between October 2024 and December 2025. The primary economic outcome was marginal profit rate (MPR), defined as the proportion of reimbursement revenue remaining after subtraction of institutionally standardized running costs. These running costs included materials, personnel, and time-based operating room allocations. Fixed costs, including capital investment, lease-related cost, and depreciation, were excluded to focus on procedural cost efficiency during routine clinical operation. Because this study was designed as a descriptive cost-accounting analysis, no formal hypothesis testing was performed; however, 95% confidence intervals (CIs) were calculated for descriptive transparency. In an additional subgroup analysis, multi-port robotic cases were separated into da Vinci Xi and da Vinci 5. Of the 607 colorectal resections initially assessed during the study period, 575 cases were included in the final analysis. In the original platform-level comparison, laparoscopic surgery showed the highest marginal profit rates across evaluated procedures. Among robotic approaches, the SP group showed numerically higher marginal profit rates than the pooled multi-port group in colectomy and rectal resection. In the additional subgroup analysis, the cohort consisted of 118 laparoscopic cases, 131

This study looks at the impact of financial ratios on Infosys Limited's share price between 2021 and 2025. It seeks to assess the company's financial performance using important criteria including profitability, liquidity, and leverage and investigate how these ratios relate to changes in stock prices. Regression and correlation analysis are two methods used to examine data that is gathered from financial websites and yearly reports. According to the study, Return on Equity (ROE) considerably raises share prices, underscoring its significance in market value. Earnings Per Share (EPS), on the other hand, exhibits a weak link. Additionally, it mentions how outside variables like investor sentiment and the state of the economy affect share prices, giving analysts and investors important information. KEYWORDS - Financial Ratios, Share Price Movement, Return on Equity (ROE), Earnings Per Share (EPS), Profitability Analysis, Liquidity Ratio,Leverage Ratio,Correlation Analysis, Regression Analysis, Stock Market Behaviour, Infosys Limited

Economic feasibility and profitability analysis of scCO2-based gold recovery process from waste printed circuit boards.

Retraction: Inclined analysis of water diversion project supply chain profits in the occurrence of whole supply chain damage in undeveloped regions of China.

High energy consumption in winter greenhouses poses a challenge to agricultural sustainability in Northern China, where heating costs typically account for 40–60% of total operating expenses. This study integrated a non-linear cost–volume–profit (CVP) analysis and data envelopment analysis (DEA) to balance cucumber yields with escalating energy costs. A single-season, single-factor experiment was conducted using insulated greenhouse compartments to evaluate four night temperature gradients (10 °C, 13 °C, 16 °C, and 19 °C). Results showed that although the 19 °C treatment (T3) achieved the highest marketable yield, it was associated with lower economic return because heating costs increased disproportionately. Among the four tested nighttime temperatures, the 16 °C treatment (T2) showed the most favorable observed combination of yield, net profit, and DEA-based efficiency indicators under the present experimental conditions. However, because the experiment was conducted in a single season within a compartment-based greenhouse system and the CVP relationship was fitted using treatment-level means, this result should be interpreted as a preliminary and condition-specific finding rather than as definitive evidence of a universal optimum temperature. Accordingly, the integrated bio-economic framework presented here is best viewed as an analytical prototype that merits further validation across multiple seasons, cultivars, and greenhouse systems.

ABSTRACT The Goods and Services Tax (GST), implemented in India on July 1, 2017, represents one of the most significant tax reforms since India's independence, subsuming over 17 central and state indirect taxes into a unified, destination-based taxation system. Micro, Small and Medium Enterprises (MSMEs), which collectively contribute approximately 30% to India's GDP, employ over 110 million people, and account for 40–45% of total exports, have been profoundly affected by this transformation. This study analyses the impact of GST on the financial performance of MSMEs in India over the period 2021–2025, using secondary financial data from five representative MSME companies. Employing trend analysis, common size analysis, comparative analysis, and profit and loss analysis, the study evaluates key financial parameters, including profitability, liquidity, cost structure, working capital management, and compliance costs. The findings reveal that while GST has imposed significant short-term compliance burdens—particularly on smaller enterprises—its long-term net financial impact is positive, with most companies demonstrating improved profitability, reduced debt, expanding asset bases, and stronger internal reserves. The study identifies digital adoption and efficient working capital management as key differentiators of GST performance outcomes and concludes with policy recommendations for the government and strategic suggestions for MSME owners to maximise the benefits of the GST regime. Keywords: GST, MSMEs, Financial Performance, Input Tax Credit, Compliance Costs, Profitability, Working Capital, India

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Subject. The relationship between cash flows and profits of an enterprise, manifested through the mechanisms of converting accounting profits into operating and free cash flows, which can become the basis for management regulation. Objectives. Development of a scientifically based integrated model that links the forecast of operational and free cash flows with targeted profit growth, and the formation of methodological proposals for its application. Methods. The research is based on systematic and integrated approaches, analysis, economic and mathematical modeling of profit and cash flow relationships. Regression analysis, scenario analysis, stress analysis, and dynamic optimization methods are used. Results. A comprehensive forecasting and calculation model is proposed, reflecting the pattern that profit growth is steadily achieved not only by increasing revenue and return on sales, but also by accelerating the turnover of cash and receivables, as it reduces the need for borrowed capital. The developed model combines probabilistic forecasting of cash flows with optimization of working capital and payment calendar parameters. The developed indicator makes it possible to quantify the quality of profit transformation into free cash flow and use it as a target standard in decision-making. The formulated risk-oriented formulation of the task of maximizing the expected profit with limitations on the risk of a cash gap ensures reproducibility and sustainability of the decisions made. Conclusions. Sustainable profit growth in modern conditions requires a transition from separate profit and liquidity management to an integrated forecasting and management circuit, in which cash flow is not a secondary consequence of profit, but an independent regulated variable that affects the cost of capital and the final net profit.

Profitability analysis is an important tool used to understand the earning capacity and financial strength of a company. It helps in evaluating how efficiently a company utilizes its resources to generate profits and sustain its business operations. By examining various financial indicators, profitability analysis provides insights into the operational performance and overall financial health of an organization. This study focuses on analyzing the profitability position of India Cements Ltd by examining its financial statements. The analysis aims to assess how effectively the company manages its resources and generates profits over a period of time. Through this evaluation, the study seeks to understand the financial performance of the company and identify its strengths and areas for improvement.

Cashew cultivation plays a vital role in the horticultural economy of Konkan region of Maharashtra and supports rural livelihoods through production, processing, and trade. This study provides a farm-level economic assessment of the cost and profitability of cashew cultivation in South Konkan region of Maharashtra. A multistage sampling framework was employed to select 120 cashew growers from Ratnagiri and Sindhudurg districts during the agricultural year 2023–24. Primary data were collected through personal interviews using a structured and pre-tested schedule. Cost of cultivation was estimated using Cost-A, Cost-B and Cost-C concept, while economic performance was evaluated through gross returns, net returns and benefit cost ratios. The findings show that the average total cost of cultivation (Cost-C) was ₹98,903 per hectare. Major cost components included the rental value of land, labour expenses and amortization cost associated with orchard establishment. The average yield was 14.76 quintals per hectare, resulting in gross returns of ₹1,76,330 per hectare. The benefit cost ratio over Cost-C was estimated at 1.78, indicating favourable economic returns from cashew cultivation in the region. A district-level comparison suggests that Sindhudurg recorded slightly higher productivity and profitability than Ratnagiri.

Mango cultivation plays a significant role in the horticultural economy of Konkan region of Maharashtra and provides an important source of livelihood for farmers. The present study examines the cost structure and profitability of mango cultivation in the South Konkan region, comprising Ratnagiri and Sindhudurg districts. A multistage sampling design was adopted to select 120 mango growers from six tahsils and twelve villages. Primary data were collected through personal interviews using a structured and pre-tested interview schedule during the agricultural year 2023–24. Standard cost concept, namely Cost-A, Cost-B, and Cost-C, was employed to estimate the cost of cultivation and profitability. The results indicated that the total cost of cultivation (Cost-C) was ₹2,29,781 per hectare in Ratnagiri and ₹2,31,953 per hectare in Sindhudurg, with a regional average of ₹2,30,837 per hectare. Hired human labour, rental value of land, and amortization cost constituted the major components of total production cost. The average yield was 31.83 quintals per hectare, generating gross returns of ₹4,09,986 per hectare. The benefit-cost ratio over Cost-C was 1.78, indicating that mango cultivation in the South Konkan region is economically viable, with relatively higher profitability observed in Sindhudurg district.

Power BI-Based and Machine Learning for Sales Forecasting and Profitability Analysis for Retail Businesses

ABSTRACT The Indian steel industry forms a vital pillar of the nation’s infrastructure and economic development, contributing significantly to industrial growth and employment generation. Among the major players, JSW Steel and Tata Steel stand as two dominant forces that shape the competitive landscape of the sector. This study seeks to undertake a comparative analysis of the financial performance of JSW Steel and Tata Steel to understand their operational efficiency, profitability, liquidity, and overall financial stability. By examining these parameters, the research aims to provide valuable insights into corporate performance and investor decision-making in the Indian steel sector. The objectives of this study include analyzing revenue and total income trends of both companies to gauge their market performance; comparing total expenses and net profit or loss to assess the impact of cost management on profitability; evaluating profit before and after tax to measure earning capability; examining total equity trends to determine the strength of shareholder funds; and analyzing current assets, current liabilities, and working capital ratios to understand liquidity and short-term solvency. Furthermore, the study measures Return on Equity (ROE) to evaluate how effectively each company utilizes shareholder investments to generate profit. A descriptive research approach based on secondary data has been employed for this study. The analysis relies on financial statements and annual reports of JSW Steel and Tata Steel covering the period from FY2022 to FY2024. The study uses key financial indicators such as revenue from operations, profit before and after tax, total equity, working capital ratio, and return on equity to perform trend and ratio analyses. These tools help identify patterns of growth, profitability, and financial health over time. The findings reveal distinct differences in financial performance between the two companies. JSW Steel displayed consistent growth in revenue during FY2022–FY2024, while Tata Steel experienced a steady decline in revenue across the same period. Although JSW Steel’s expenses rose moderately, the company managed to sustain profits. In contrast, Tata Steel’s expenses increased faster than its income, leading to losses by FY2024. Profitability analysis indicated that while JSW Steel’s profits declined, they remained positive, whereas Tata Steel’s profit margins deteriorated significantly, culminating in a net loss. In terms of working capital management, JSW Steel maintained a stable working capital ratio, reflecting efficient short-term financial management and liquidity control. Tata Steel, however, showed a sharp fall in its working capital ratio, signaling rising financial strain. Similarly, JSW Steel’s total equity improved by FY2024, implying enhanced shareholder value and financial resilience. On the other hand, Tata Steel’s equity declined consistently, reflecting reduced investor confidence and weakening financial strength. The Return on Equity analysis further reinforced these findings: JSW Steel sustained positive ROE, though declining slightly, while Tata Steel’s ROE turned negative by FY2024, indicating poor utilization of shareholders’ funds. In conclusion, the comparative analysis highlights JSW Steel’s stronger and more resilient financial performance compared to Tata Steel during the study period. Effective cost management, liquidity control, and stable equity growth enabled JSW Steel to sustain profitability, while Tata Steel’s financial position weakened due to declining revenues and rising expenses. The study emphasizes the importance of strategic financial management in maintaining competitiveness and long-term sustainability in India’s steel industry. Keywords: Financial Performance, Working Capital Management, Return on Equity, Steel Industry Analysis, Profitability Trends