Distribution Companies Research Articles

Prioritizing project risks by a transdisciplinary approach using the grey ordinal priority approach: A case study of an electricity distribution company

Prioritizing project risks by a transdisciplinary approach using the grey ordinal priority approach: A case study of an electricity distribution company

Evaluating the Financial Performance of Retail Oil Distribution Companies in India: A Comparative Study of Public and Private Sectors

This study examines the financial performance of public and private sector retail oil distribution companies in India from 2013 to 2023. The research focuses on two hypotheses: first, that private sector companies (RIL and Nayara Energy) demonstrate superior profitability metrics (ROCE, ROA, ROE) compared to public sector counterparts (BPCL, HPCL, IOCL) due to operational flexibility and market-driven strategies; and second, public sector companies exhibit lower financial leverage (Debt-Equity Ratio) reflecting conservative financial management and government oversight. Statistical tools such as ANOVA were employed to analyse ten years of financial data, revealing significant differences in profitability metrics favouring private-sector companies, and lower financial leverage among public-sector entities. These findings provide investors, policymakers, and stakeholders valuable insights in understanding sectoral dynamics and making informed decisions. The study contributes to the existing literature by illustrating distinct financial strategies and performance trends within India's retail oil distribution sector, crucial for strategic planning and regulatory frameworks in the energy industry.

Film Policy and Film Distribution: The Case of the Baltic Film Industries

Abstract The aim of the study is to analyse the development of the Baltic film distribution markets and to provide new recommendations for its potential growth based on mission economy approach and bigger role of the states in co-creating and co-shaping the markets especially for the Baltic co-production of films and their distribution. The study used both qualitative and quantitative methods for data extraction and analysis. Firstly, descriptive statistics as a method was used to analyse the market shares of the main film distribution companies in Lithuanian, Latvian and Estonian film industries. Furthermore, 5 semi-structured interviews with experts from the Baltic film industries were conducted. As a result of the research, the author concludes that there is a potential in family genre films that are produced in the Baltic States, but in general the Baltic co-production films lack quality, storytelling that would arouse the interest of the audience and potentially new regional film fund “Baltic Film and TV Fund” would have to focus not only on increased financing for co-productions, but also on other measures that would help to produce better quality genre films including co-productions and their distribution.

ORGANIZATIONAL AND FINANCIAL ASPECTS OF DISTRIBUTION MANAGEMENT OF DIGITAL CONTENT

In today's crisis conditions caused by military, financial, economic, social, environmental political upheavals and threats, the role of innovative technologies in trade is growing significantly. First of all, this applies to digital distribution in the book trade. Compared to traditional forms of trade, it does not require extensive infrastructure, large production facilities, or numerous staff. This helps to reduce transaction costs, respond more quickly to changing market conditions and simplify access to international trading platforms. However, the further development of digital distribution requires constant monitoring and analysis of global trends, and implementation of the best domestic and foreign practices to ensure efficient management of trading operations.The purpose of the study is to formulate the main financial and organizational measures to improve the management of digital distribution and increase its efficiency. To achieve this goal, the following tasks were solved: based on scientific publications and statistical data, the author monitored the trends in the development of digital distribution and the e-book market in Ukraine and in the world; analyzed the rank and level of visits to the websites of leading online e-book and audiobook stores in Ukraine; identified external and internal factors that affect the efficiency of digital distribution, in particular, e-books and audiobooks in the current conditions of military aggression and other risks; developed a model for generating revenue for a digital distribution platform.Financial, economic and organizational measures to improve the company's distribution management of digital content are proposed. These include areas of customer incentives and rewards, improved communication with digital goods manufacturers, priority funding for projects to improve the platform interface and mobile application, improved accounting, reporting, operational and strategic planning, and the introduction of artificial intelligence.

Service center in electricity distribution sector with variable peak electricity time: A two-stage queuing model approach with nested simulation

Customer service is essential for any business, significantly impacting customer satisfaction, brand reputation, and reducing associated costs. In the electricity industry, this importance is heightened due to the critical nature of electricity in daily life and growing usage rate of new technologies. Effective customer service in electric distribution companies involves handling a wide range of inquiries, from billing issues to technical support, requiring both remote and on-site assistance. The variability in customer calls, influenced by factors such as peak electricity hours, and different service and customer types, presents unique challenges in designing efficient service centers. This research develops a tailored model for the service center operations of a power distribution company, focusing on optimal staffing levels within budget constraints. A two-stage queuing model is proposed to address the needs of residential and non-residential customers. The study employs nested simulation techniques to account for variability in customer arrival times and peak hours. Key performance indicators (KPIs) are used to evaluate the effectiveness of staffing policies, considering both quantitative and qualitative costs. The study integrates stochastic optimization and ranking and selection methods to identify the best staffing configurations. The findings offer actionable insights for improving customer service efficiency and operational effectiveness in electricity customer service centers.

Cultivating inclusive leadership: a catalyst for enhanced organizational citizenship

Purpose The present manuscript aims to develop and validate a theoretical model capable of explaining that organizational citizenship behavior is influenced by the extent to which employees feel valued, accepted and considered integral to the organizational fabric. To do this, the authors draw on social identity theory, according to which the level of identification of a person with a group or organization is not fixed but situational and context-dependent. Design/methodology/approach To validate the theoretical model, the authors surveyed the employees of eight large-scale distribution companies operating in Italy. Overall, the authors received completed data from 2,010 employees. Findings The authors theorize and demonstrate that the presence of an inclusive corporate climate positively influences employees’ perceptions of work inclusion and that this latter, in turn, positively affects organizational citizenship behavior. Furthermore, they show that the indirect effect of an inclusive corporate climate on organizational citizenship behavior becomes stronger when inclusive leadership is promoted within an organization. Originality/value Overall, this paper confirms social identity theory in a novel way. Social identity theory suggests that the context can impact an employee’s identification with the organization they work for, without specifying the characteristics that the context must possess. The authors’ contribution reaffirms this theory by proposing that it is specifically the inclusiveness of the context that positively influences the employee’s identification within the organization. By focusing on this aspect of inclusion, this research introduces a novel perspective that enriches the current discourse on OCB and underscores the importance of cultivating inclusive workplace environments. Also, the authors add theoretical nuance to previous literature by suggesting that the way top management exercises leadership over employees can amplify the strength of corporate climate influence on worker inclusion perception.

Overview of Financial Efficiency in India’s Power Sector

Power is an important tool for economic growth of the country. Power is vital for every form of human activity-domestic, agricultural and industrial infrastructure, such as telecommunication and transport. The demand for electricity in India is enormous and is growing steadily. This growth has been slower than a country’s economic growth. The big challenge of the power industry is to balance the demand and supply of electricity. Financial management involves planning, organizing, directing, and controlling the financial activities of an organization. Its primary goal is to maximize shareholder wealth and ensure the efficient use of resources. Financial efficiency refers to how effectively an organization utilizes its resources to generate revenue or profits. It involves minimizing costs and maximizing output or outcomes relative to inputs. The financial efficiency of India's power sector is a critical aspect of its energy infrastructure, impacting both economic growth and sustainability. The main needs of the study are the source and use of funds of the company and how to evaluate the financial performance of the company. The objective of this study is to critically evaluate and assess the financial performance of Southern Power Distribution Company of Andhra Pradesh State Limited, Tirupati.

Demand Response Strategies among Power Distribution Companies for Efficient Power System Management in Nigeria

This study investigates the demand response strategies employed by power distribution companies (DisCos) in Nigeria and their implications for efficient power system management. As the Nigerian power sector grapples with persistent inefficiencies and reliability issues, implementing effective demand response mechanisms emerges as a crucial strategy for improving overall performance. The research employs a quantitative methodology, utilizing a structured questionnaire administered to a sample of 316 stakeholders across various DisCos in Nigeria. Findings reveal a significant relationship between the implementation of demand response strategies and the efficiency of the power system (p < 0.05), indicating that such strategies can enhance operational efficiency. Moreover, the adoption of advanced metering infrastructure is shown to significantly improve the effectiveness of these strategies, underscoring the importance of technological integration in power distribution. However, the study also identifies key challenges faced by DisCos, such as regulatory hurdles and inadequate infrastructure, which hinder the adoption of demand response initiatives.

An investigation on NGR failure in Indian smart cities while replacing the existing overhead lines by underground cables

Abstract Nowadays, Indian power distribution companies (PDCs) are implementing smart distribution networks. Older cities are becoming smarter as per the recent government’s policy. Existing overhead distribution lines are being replaced by underground cables as an essential criterion of a smart city. One of the main problems arising in this process is the overheating of the neutral grounding resistor (NGR) in 11 kV distribution systems, even in normal conditions. NGRs, placed inside the substations, are overloading the air conditioning and exhaust systems of the substation. Sometimes failure of the NGR occurs due to overheating. In this paper, a comprehensive investigation has been carried out to reach the roots of this problem. It is observed that long underground cables have a higher ground capacitance than overhead distribution lines. Due to the higher cable capacitance, the third harmonic current circulates through neutral, which overheats the NGR even in normal conditions. The situation becomes worse when the substation runs on diesel generators (DGs) in an isolated state under main grid failure, as a higher amount of third-harmonic current circulates depending on the type of winding and pitch factor of the DGs. Different solutions are proposed, and their advantages and disadvantages are analyzed. Finally, the rating of the NGR is modified, and louvers-cooling fan arrangement is preferred for the running substation.

Mediation Role of Job Satisfaction on Employee Performance A Study on Distribution Company

This study explores how career development, competence, and compensation influence employee performance, with job satisfaction serving as a mediating factor. According to data from the Central Bureau of Statistics (BPS), there are 2,153 distributor companies in Batam City, employing 259,749 workers. The study sampled employees from these companies, collecting data from 387 respondents via online questionnaires distributed through Google Forms. Out of these, 313 responses were valid and analyzed, while 74 were discarded due to invalidity. The majority of respondents were female (54.63%), with males making up 45.37%. The research employs a descriptive quantitative approach, using quantitative data analysis techniques. The sampling method involved surveys with 29 questions, and data were processed using the Partial Least Square (PLS) application. The study tested 10 hypotheses: seven examining direct relationships (H1-H7) and three examining indirect relationships (H8-H10). The findings reveal that nine out of the ten hypotheses were supported with significant positive results, while one hypothesis specifically H1, which proposed that career development impacts employee performance was not supported.

Advancements in NEEA'S methodology for calculating regulatory operating costs of electricity distribution companies based on PC 062/2020

Advancements in NEEA'S methodology for calculating regulatory operating costs of electricity distribution companies based on PC 062/2020

Energy subsidies: conceptual framework and measurement for distributional impacts in Argentina

Argentina has massively subsidized energy in recent decades, and the distributional impacts of those subsidies has been widely studied. However, regional disparities and public financing are two dimensions often omitted by previous research. We extend the analysis in these directions, focusing on the electricity sector. First, we develop a conceptual framework to formalize the deviation of prices from production costs. Second, by applying the “benefit incidence analysis” to household survey microdata, we measure subsidies at the household level and perform a distributional analysis. Our results indicate that regional disparities in electricity distribution costs and in the pricing schedules set by distribution companies are key drivers of the distributional impacts. Subsidies, as a percentage of the final price, vary between regions in the range of 50 to 80 percent. Additionally, omitting public financing leads to a bias in the perception of their redistributive effect: when subsidies are financed by a general consumption tax, the net benefits are less than half of the benefits from the subsidy alone. A series of globally relevant policy recommendations can be derived from the paper.

Cost - benefit analysis of DISCOs by Optimal allocation of DGs and DSTATCOM using GTO algorithm

Electric power Distribution Companies (DISCOs) provide low-cost, reliable, and consistent voltage power from distribution substations. DISCOs have radial transmission lines with all buses as load buses and no generating buses. The voltage at each bus decreases, resulting in larger network losses and voltage variations, which lowers DISCO and customer costs and benefits. This study strategically uses Distributed Generation (DGs) and DSTATCOM to optimize cost-benefit analysis and voltage stability for Distribution Companies (DISCOs). We planned DG unit and DSTATCOM deployment using a new and comprehensive Group Teaching Optimization (GTO) method in this study. The algorithm considers Distribution Company and DG Owner profitability simultaneously. Group Teaching Optimization (GTO) is used on a 33-node test system. MATLAB simulations show the GTO's usefulness in Distribution System Operators.

Applying Neural Networks to Predict Ventilator Demand: A Study of Pakistan's Healthcare Sector

The distribution companies that deal with ventilators in Pakistan face challenges related to inventory control because of inadequate product shelf life, shortages, excess inventory, and unnecessary stock. This study, which focuses on Pakistani ventilator distribution companies, aims to offer a novel approach to sales estimation, avoid unnecessary stock expenditures, and stop clientele loss brought on by ventilator shortages. The results of this study will help determine key elements and standards that Pakistani distributors of ventilators might employ to boost sales. Most ventilator distribution businesses in Pakistan are independent wholesalers that purchase stock from their stores and distribute it to customers. To maximize ventilator distribution firms' sales for various products, this study examined distribution and sales data from 2019 to 2024 for many locations and dates. To create an accurate sales forecasting model for a ventilator distribution company, this research also aims to apply artificial neural networks (ANN) for effective sales prediction. An Artificial Neural Network (ANN) model was trained using a dataset from ventilator distribution businesses and the proposed model produced an accuracy of 90%, which is good for early prediction.

Iterative LMI-Tuned PID Controller for Robust Decentralized Multi-Area Automatic Generation Control in Deregulated Electricity Markets

This study proposes an Iterative Linear Matrix Inequality (LMI)-Tuned Proportional-Integral-Derivative (PID) controller for robust decentralized AGC in the context of deregulated electricity markets. The study addresses the challenges posed by market uncertainties and diverse generation sources, aiming to enhance the stability and performance of power systems. This study is driven by the urgent need to develop robust AGC strategies that are adapted to the complex dynamics of decentralized power systems operating in deregulated markets. The conventional centralized control approaches are often inadequate to address the diverse and distributed nature of modern generation units. Furthermore, the intermittent and variable nature of renewable energy sources adds a layer of complexity that demands innovative control solutions. The impact of bilateral contracts on the dynamics is taken into consideration while modifying the conventional LFC of interconnected power networks. To model these bilateral contracts, the distribution company (DISCO) participation matrix (DPM) is presented, and the multi-area block diagram reflects these concepts. Simulation studies are conducted to evaluate and compare the performance of the proposed Iterative LMI-Tuned PID Controller and Conventional PID Controller. Results are analyzed against key performance metrics, considering scenarios reflective of diverse market conditions. Comparative studies with the conventional PID controller provide insights into the efficacy and robustness of the proposed approach.

Comparison of Djikstra, Hybrid-PSO algorithms for optimizing the distribution route of papaya seeds and honey products (Case Study: PT. Agro Apiari Mandiri)

Dynamic global competencies in the industrial sector drive fierce competition in capturing markets and increasing customer satisfaction, which requires efficiency in various aspects of business including distribution. PT. Agro Apiari Mandiri faces challenges in optimizing delivery routes to avoid delays. This study aims to compare the Dijkstra and Hybrid-PSO algorithms to determine the optimal distribution route in the Bogor, West Java, and Lebak, Banten regions, in order to reduce the distance and delivery time. The research methods include literature study, data collection, and route optimization model creation. The results show that PSO is more efficient in optimizing delivery routes than other methods, with variations in PSO parameters affecting total travel time, number of vehicles, and computing time. Implementation uses hardware and software such as MSI Laptops and Matlab. In conclusion, the use of PSO in distribution route optimization makes a significant contribution to the company's cost and distribution efficiency and can be a reference for further research in distribution route optimization.

Developing and Implementing an Artificial Intelligence (AI)-Driven System For Electricity Theft Detection

Electricity theft is a significant challenge for utility companies worldwide, leading to substantial economic losses and inefficiencies in power distribution. Traditional methods of detecting electricity theft, such as manual inspections and routine audits, are often inefficient and ineffective. To address this issue, this study aims to develop and implement an artificial intelligence (AI)-driven system for electricity theft detection. Methodology used are data collection, data analysis, feature selection with Chi-Square, feature transformation with Principal Component Analysis (PCA), Support Vector Machine (SVM) and model for electricity theft detection. To achieve this, a Particle Swarm Optimization Algorithm (PSO) was applied to improve training performance of the SVM, using data of meter recharge information collected from Enugu Electricity Distribution Company (EEDC). The system effectiveness is validated through extensive testing using real-world data from various regions and scenarios, demonstrating its robustness and adaptability. The system result considering FDR reported that 0.11 was achieved for the particle swarm based SVM model. When TPR was considered for analysis, it was observed that particle swarm based SVM attained a score of 0.89. In addition, Particle swarm based SVM attained PPV of 0.895. In terms of accuracy, the particle swarm based SVM reported an accuracy of 0.857. The result showed that the particle swarm based SVM performed better from the system validation achieved through comparative analysis, hence it is recommended for use to develop the new software for energy theft investigation. The implementation of this AI-driven solution offers numerous benefits, including enhanced detection accuracy, reduced operational costs, and improved overall efficiency of power distribution networks. Moreover, it enables utility companies to take proactive measures to prevent theft, ensuring a more reliable and secure electricity supply for consumers.

An Evolutionary Game Model of Market Participants and Government in Carbon Trading Markets with Virtual Power Plant Strategies

The utilization of conventional energy sources commonly leads to heightened energy consumption and the generation of specific forms of environmental pollution. As an innovative power management and dispatch system, virtual power plants (VPPs) have the potential to significantly enhance the flexibility and stability of power systems, while supporting carbon reduction targets by integrating distributed energy resources (DERs), energy management systems (EMSs), and energy storage systems (ESSs), which have attracted much attention in the power industry in recent years. Consequently, it can effectively address the variability and management challenges introduced by renewable energy. Furthermore, optimizing power market dispatch and user-side power management plays a pivotal role in promoting the transition of the energy industry towards sustainable development. The current study highlights the unresolved issue of strategic decision-making among market participants, such as energy companies, generation companies, and power distribution companies, despite the potentially significant benefits of VPPs. These entities must carefully evaluate the costs and benefits associated with adopting a VPP. Additionally, governments face the complex task of assessing the feasibility and effectiveness of providing subsidies to incentivize VPP adoption. Previous research has not adequately explored the long-term evolution of these decisions in a dynamic market environment, leading to a lack of adequate understanding of optimal strategies for market participants and regulators. This paper addresses this critical research gap by introducing an innovative bilateral evolutionary game model that integrates VPP and carbon trading markets. By utilizing the model, simulation experiments are carried out to compare different strategic decisions and analyze the stability and long-term evolution of these strategies. Research findings indicate that the adoption of VPP technology by market participants, in conjunction with government policies, results in an average 90% increase in market participants’ earnings, while government revenues see a 35% rise. This approach provides an alternative method for understanding the dynamic interactions between market participants and government policy, offering both theoretical and practical insights. The findings significantly contribute to the literature by proposing a robust framework for integrating VPPs into electricity markets, while offering valuable guidance to policymakers and market participants in developing effective strategies to support the sustainable energy transition. The application of this model has not only enhanced the understanding of market dynamics in theory, but also provided quantitative support for strategic decisions under different market conditions in practice.

Urban Sharing Logistics Strategies against Epidemic Outbreaks: Its Feasibility and Sustainability

Epidemic (e.g., COVID-19) outbreaks can seriously disrupt logistics, and the coordination of intercity logistics and urban distribution plays an important role in goods distribution. In previous studies, some scholars analyzed different sharing logistics mechanisms for cost reduction and efficiency improvement, while others analyzed the disruption problems in both logistics and supply chain management. In this study, we combine these two operational management philosophies and first develop a two-echelon logistics benchmark model (BM), with two intercity logistics companies and two urban distribution companies, taking into consideration the load ratio and the disruption factor. This is the first time that the load ratio is considered in research on logistics, and it will make the supply and demand as well as the cost structure of logistics services much more practical. We then develop three urban sharing logistics models with two intercity logistics companies and one urban sharing logistics distribution company, with the sharing mechanisms SM1 (only sharing logistics), SM2 (sharing logistics with revenue sharing), and SM3 (sharing logistics with equity investment). We compare the pros and cons of the three sharing mechanisms and identify the optimal and suboptimal Pareto improvements for the BM. We identify different sharing decisions with respect to different load ratios and the disruption ratio. Finally, we analyze the sustainability of the three sharing mechanisms from the load ratio, low-carbon, and low-disruption dimensions. The managerial implications drawn from the model and case study provide a practice framework for sharing logistics operations: vertical integration, the standardization of logistics technology and equipment, and coordination and sharing.

Pengoptimalan Rute untuk Minimasi Biaya Distribusi pada CV.DNY

The distribution route problem at CV.DNY is related to the lack of optimal route determination because delivery routes are determined only based on the order of goods received first. Determining the route in the distribution process is an important factor for the company because it affects the company's distribution costs. CV. DNY is a logistics company that operates in the sector of delivering goods to consumers. Based on field studies conducted, the company has not been able to determine the optimal route. The aim of this study is to increase the efficiency of the routes used so that shipping costs can be saved. The method used in this research is a minimum spanning tree. The results of the research show that the minimum spanning tree method obtains a shorter route with a distance of 4557 km compared to the company's initial route of 5318 km, experiencing distance savings of 761 km and minimizing distribution costs of IDR 5,174,800. So it can be concluded that the minimum spanning tree method uses POM-software The company's QM (Program Operations Management – ​​Quantitive Method) achieves delivery route savings and cost minimization.