Company Sales Research Articles

Analysis of the relevance and prospects of application of federate training

This article examines federated learning (FOE) as an innovative approach to machine learning, different from traditional methods. In conventional machine learning (MO), data is collected on a central server to train the model. However, in the case of FO, the learning model is directed to data distributed across local devices, and learning takes place directly on these devices. In addition, the article discusses methods and algorithms of federated learning, identifies the advantages and real areas of application of federated learning. FO is used in various fields, including working with medical data and personal data of customers in sales companies. This approach is especially valuable for ensuring data confidentiality and privacy.

The Influence of Company Size, Business Risk, and Sales Growth on Capital Structure Mediated by Profitability

This study aimed to determine the effect of company size, business risk, and sales growth on capital structure with profitability as an intervening variable on the JII stock index on the Indonesia Stock Exchange (IDX) from 2017 to 2021. The method used to determine the research sample is purposive sampling. The source of data in this research is secondary data. Data analysis techniques used path analysis, t-test (partial), and Sobel test (mediation) using SPSS version 23. The study's results stated that company size, sales growth, and profitability have a significant effect on capital structure while business risk has no significant effect on capital structure. Company size, business risk, and sales growth significantly affect profitability. The Sobel test results state that company size, business risk, and sales growth have a significant effect on capital structure mediated by profitability, meaning that mediation occurs.

Peran Strategi Pemasaran Dalam Meningkatkan Omzet Penjualan Nymaz Hijab Kecamatan Ngasem Kabupaten Kediri

This study aims to examine the role of marketing strategies in increasing the sales turnover of Nymaz Hijab products in Ngasem District, Kediri Regency. This research uses a qualitative method using primary data obtained from interviews and direct observation with the owner, employees, and consumers of Nymaz Hijab. Secondary data used is information from the internet and Nymaz Hijab's social media accounts. The results showed that Nymaz Hijab uses marketing strategies which include attention to product quality, always updating products, determining prices based on product prices from the center by considering other costs, and active promotion through social media such as Instagram, WhatsApp, and TikTok. However, Nymaz Hijab needs to pay attention to market selection to determine its target market. With the marketing strategy carried out, Nymaz Hijab succeeded in increasing sales turnover from IDR 278,050,000 in 2022 to IDR 289,950,000 in 2023. In addition, business owners also sometimes hold product sales to attract consumer interest. Thus, an optimized marketing strategy can make a significant contribution in increasing the company's sales turnover.

The Influence of Production Costs and Sales Volume on Company Profits at PT Solusi Bangun Indonesia (Case Study on the Indonesian Stock Exchange 2015-2022)

In 2019, production costs decreased by IDR 1,858,167. The decrease in production costs is because the company has to pay Holcim's debt, whose total debt reaches 9 trillion, so this year production costs have decreased. The lowest sales volume occurred in 2017. In 2017, the company's sales volume was only IDR 2,158,795. The decline in sales volume was caused by falling production costs and high inflation which also caused an increase in commodity prices. The lowest net income occurred in 2017. In 2017, the company still experienced a financial year loss (863,644) rupees. The decrease in operating profit was caused by a decrease in sales figures and a relatively large increase in financial costs

ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI MANAJEMEN LABA PADA PERUSAHAAN SAWIT DI INDONESIA

This research aims to explore the impact of Profitability, Company Size, Leverage and Sales Growth on Profit Management in Palm Oil Companies. The method used in this research is Weighted Least Square using IBM SPSS as the application. Data collection techniques are carried out through documentation methods. The data used in this research is secondary data obtained from the Indonesian Stock Exchange or related company internet sites. The research sample consists of 12 companies listed on the Indonesia Stock Exchange during the period 2017 to 2021. The research results show that the variables Profitability and Leverage have a significant negative influence on Profit Management, while Company size and Sales Growth do not have a significant influence on Profit Management.

Business Strategy, Short-Term Debt, and Cost Stickiness

This research delves into the dynamics that underlie the relationship between changes in a company's sales and its cost structure. It also explores the influence of short-term debt, often associated with sales, on a phenomenon known as cost stickiness. Furthermore, we examine the roles of product market competition and various business strategies in shaping these interactions. We used financial data from 153 companies listed on the Tehran Stock Exchange from 2015 to 2021 to conduct a rigorous regression analysis to unearth significant insights. Our findings reveal that short-term debt serves as a mechanism for companies to effectively manage their financial obligations with lenders and creditors, and it is inversely correlated with cost stickiness. Moreover, our results shed light on how the impact of short-term debt on cost stickiness varies in response to the competitive nature of the product market and a company's chosen business strategy. Specifically, when companies adopt a "prospector strategy" to explore new markets and expand their product offerings, the negative association between short-term debt and cost stickiness weakens. In a broader context, our study contributes to comprehending cost stickiness and carries practical implications for industry professionals and future scholarly pursuits.

ANALISIS PENYUSUNAN ANGGARAN PENJUALAN PADA UMKM KULINER SEBLAK RANCAEKEK

This research was conducted because there was no budget in the financial records of Seblak Rancaekek Culinary MSMEs, especially the sales budget where the sales budget is a budget that plans the company's sales for the coming period. The sales budget is used as a company tool in planning and controlling the company's sales activities in order to achieve the desired optimal profit. The sales budget can be used as a reference in efforts to increase subsequent sales. In making sales forecasts, researchers compared 3 forecasting methods, namely Semi Average, Trend Moment, and Least Square and calculated the Standard Forecasting Error (SKP) for each method to determine the most appropriate method.

Conformalized prescriptive machine learning for uncertainty-aware automated decision making: the case of goodwill requests

AbstractDue to the inherent presence of uncertainty in machine learning (ML) systems, the usage of ML is until now out of scope for many critical (financial) business processes. One such process is goodwill assessment at car manufacturers, where a large part of goodwill cases is still assessed manually by human experts. To increase the degree of automation while still providing an overall reliable assessment service, we propose a selective uncertainty-aware automated decision making approach based on uncertainty quantification through conformal prediction. In our approach, goodwill requests are still shifted to human experts in case the risk of a wrong assessment is too high. Nevertheless, ML can be introduced into the process with reduced and controllable risk. We hereby determine the risk of wrong ML assessments through two hierarchical conformal predictors that make use of the prediction set and interval size as the main criteria for quantifying uncertainty. We also utilize conformal prediction’s property to output empty prediction sets if no prediction is significant enough and abstain from an automatic decision in that case. Instead of providing mathematical guarantees for limited risk, we focus on the risk vs. degree of automation trade-off and how a business decision maker can select in an a posteriori fashion a trade-off that best suits the business problem at hand from a set of pareto optimal solutions. We also show empirically on a goodwill data set of a BMW National Sales Company that by only selecting certain requests for automated decision making we can significantly increase the accuracy of automatically processed requests. For instance, from 92 to 98% for labor and from 90 to 98% for parts contributions respectively, while still maintaining a degree of automation of approximately 70%.

Victoria’s Secret: the falling angels

Research methodology Secondary research Case overview/synopsis Victoria’s Secret, a lingerie retailer founded by Roy Raymond in 1977, is the largest retailer in women’s intimate apparel in North America. Nevertheless, the business has been under fire in the recent past for failing to be inclusive and diverse, declining revenues and engaging in high-profile controversies. Victoria's Secret has experienced competition from emerging lingerie brands including Savage X Fenty, which Rihanna established in 2018, ThirdLove and Aerie by American Eagle & Knix. Victoria's Secret tried to reinvent itself in reaction to these difficulties by altering its marketing approach, switching out its “angels” for more diversified models, and launching a new range of cozy, informal loungewear. However, there were conflicting reactions to these initiatives, and the company's sales have been declining. Complexity academic level Executive training programs, upper level undergraduate and graduate MBA students in strategic, marketing and general management. Students should understand the basics of strategic management and marketing before undertaking to analyse this case.

Prospects and challenges in logistics management of international companies

Inventory management models are aimed at establishing optimal batch sizes of resources that will be subsequently used in the production process. The author believes that the use of this model makes it possible to set order sizes not «manually» by employees of the supply department, but rely on an optimization economic and mathematical model. Considering that these calculations are given only for one item of purchased inventory items, we can conclude that expanding the use of this approach to other types of purchased parts and raw materials will contribute to greater savings in financial resources. The option proposed in the article helps to save the Company's expenses on the type of inventory under consideration by $244,4 per year compared to the original option (or by 1,3 %). Minimizing overall transportation costs will depend on optimal vehicle loading. Optimal loading of vehicles will minimize the number of vehicles involved in transportation, and therefore reduce the overall costs of delivering products to customers. The results of the work can be used to improve the Company's inventory management, as well as to solve problems of transport support for entering a new market (transport routing). The combination of ABC and XYZ analyzes will make it possible to have a visual representation of all inventories in the Company’s warehouse through the formation of standard groups of inventories, in relation to each of which the inventory management policy will be different. Considering the steady growth rate of the company's sales, the author recommends expanding the sales network by entering new markets, which could be, for example, regions of the Russian Federation.

Analysis of sales demand and production capacity to determine the need for direct labour

This study consists of meeting the sales demand using the existing production capacity in an electronic goods industry and thus determining the amount of direct labor (MOD) necessary to meet the needs of customers. Since obtaining the correct number of operators on a production line is extremely important in the pursuit of productivity and cost reduction. Therefore, using concepts such as takt time, cycle time and line efficiency and other information related to the product or products that will be assembled on a production line, it will be possible to quickly and assertively determine the number of operators that must serve directly the client's demand, thus guaranteeing productive efficiency and the correct application of labor resources using as assumptions the capacity and equipment already existing in the production line. Thus, based on the company's sales projection, it will be possible to determine month by month the number of operators, number of shifts and the appropriate volume to be produced to meet the requested demand.

Penerapan dan Analisis Metode Social Network Analysis untuk Menentukan Rekomendasi Diskon dengan Menggunakan Library NetworkX

At present technology has developed rapidly, especially in industrial technology. Business competition is getting tighter, making people have to find ways to maintain their business. One strategy that can be used is to provide discounts on goods or services sold. This discount can be made based on the company's sales data or other factors. In this case, the company has large sales data. Therefore, a way is needed to process the large sales data, and one efficient way to do this is to use the Social Network Analysis method. This study measures the degree of Information Centrality from the Social Network Analysis method to measure how much the item is purchased, this can be taken into consideration to determine discounts on goods or services sold. This research provides the results of discount recommendation applications that can process large sales data and provide recommendations based on the Social Network Analysis method.

Deteksi Kesehatan Keuangan Industri Department Store Selama Periode 2020 – 2022 Menggunakan Financial Discriminant Models Altman Z-Score

This study aims to determine the condition of the company's financial health during the 2020-2022 period. The sampling technique used is purposive sampling. This research was conducted on department store companies. The data used in this study is secondary data obtained from the websites of each company. This research tries to find the factors causing the decline in the company's liquidity level through the company's financial report data during the 2020-2022 period, based on the research conducted several factors were found to be the phenomenon of a decrease in the level of sales that occurred due to the impact of social restrictions large-scale so that it affects the company's sales level and disruption of the company's cash flow. From the results of the research conducted, the authors hypothesize several solutions that other similar companies can use in dealing with the impact of the crisis, some example is to create new market options that utilize technology such as increasing market networks and dividing the ratio of direct sales and indirect sales. Research results and theoretical implications obtained by the authors are expected to be used for the next 2-3 years after the crisis ends.

A STUDY ON DIGITAL MARKETING OF FLIPKART

Efficient digital marketing tactics are crucial for companies to succeed in the ever-changing world of e-commerce. Flipkart is one of the most prominent online marketplaces in India, and this study examines their digital marketing strategies. Examining Flipkart's strategy across different digital channels and how they affect the company's brand visibility, consumer engagement, and sales is the main objective of this research. In order to better understand how Flipkart draws in and keeps customers, as well as how to increase engagement and conversion rates, this study analyzes the company's website design and user experience. In addition, it delves into Flipkart's SEO tactics, namely its attempts to rise in the SERPs and target certain keywords. Content marketing campaigns run by Flipkart, such as blog articles, product descriptions, videos, and social media postings, are examined in the research. It delves into the ways Flipkart uses content to captivate its audience and boost sales. The research also examines Flipkart's approach to social media marketing, looking closely at the company's content and interaction tactics across sites like Facebook, Instagram, and Twitter. This study delves into Flipkart's email marketing initiatives, specifically looking at their subscriber segmentation tactics and the content of the emails they send out. Also covered is an examination of Flipkart's paid advertising campaigns, including display, search engine, and social media ads, as well as an analysis of the company's channel allocation strategies. In this case study, we take a look at how Flipkart uses mobile marketing and influencer marketing to boost engagement and sales through its app and its partnerships with influential users. It also checks Flipkart's analytics, which include how well the company uses data to monitor the efficacy of its digital advertising activities. Keywords: Flipkart, digital marketing, e-commerce, online marketplace, SEO, content marketing, social media marketing, email marketing, paid advertising, influencer marketing, mobile marketing, analytics, user experience, customer engagement, sales optimization, India.

THE EFFECT OF CHANGES IN VALUE-ADDED TAX RATES (VAT) AND COST OF GOODS SOLD (COGS) ON SALES TURNOVER AT PT. VCS

The increase in Value Added Tax (VAT) rates and the rise in Cost of Goods Sold (COGS) significantly impact the business strategy and profitability of the company. The research aims to examine the impact of the increase in VAT rate and changes in the Cost of Goods Sold on PT's business strategy and profitability. VCS. The method used is quantitative research using PT's sales data. VCS from 2018 to 2022, as the population was selected through a purposive sampling method. Data analysis was conducted using SPSS version 27. The research findings indicate that the increase in the value-added tax rate significantly impacts PT's sales revenue. VCS, while the increase in Cost of Goods Sold does not considerably affect the company's Sales Revenue

Nonpecuniary Benefits: Evidence from the Location of Private Company Sales

Abstract This paper investigates whether acquisition prices reflect a specific set of nonpecuniary benefits preferred by entrepreneurs: the quality of life (QOL) associated with the business location. Using data on private firm acquisitions, we find that target firms in high-QOL cities sell for a 14% to 20% premium. Traditional financial factors do not explain this premium, which dissipates when the buyer is unlikely to have preferences for high-QOL locations. Using wage-to-housing cost differentials to decompose local amenities and data on migration patterns, we find that QOL amenities have a greater impact on entrepreneurs’ location decisions relative to wage workers. (JEL G02, G32, G34, J32, L26, R39) Received: 27 February 2022; Editorial decision: 29 January 2024 Editor: Camelia Kuhnen Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

MENINGKATKAN OMZET PENJUALAN MELALUI PENINGKATAN KUALITAS PRODUKSI TANDAN BUAH SEGAR DI PT. MAKMUR AGRO LESTARI

PT. Makmur Agro Lestari, Ketungau Hilir District, is one of the oil palm plantations in the Sintang Regency region, which also produces fresh fruit bunches (FFB) from its own plantations. Market FFB using sustainable and quality production methods so that the company's palm sales can increase with each harvest and each year. This type of research is qualitative. Data collection involved interviews, document research, and observations. The research subjects are property managers, administrative heads and employees. The researchers analyzed the results of the interviews based on the respondents' understanding of what was expressed. The data that has been compiled must be understood as a whole so that the researcher can grasp the experiences, issues, and dynamics that are actually occurring within the population being studied. Research results show that marketing of palm products always meets FFB's sales goals. The company has cooperated with customers to sell palm products to PT. ASL - POM Agency is one of the largest buyers of palm fruit in West Kalimantan. From the quality perspective of FFB. Makmur Agro Lestari Ketungau Hilir district harvests and sells selectively, so the quality and selling price are stable according to FFB's market price when sold to purchasing companies.

Marketing Public Relations Sebagai Business Representative Dalam Meningkatkan Penjualan Dengan Metode B2B

This journal reviews the marketing public relations strategy used to increase sales with the B2B method at PT Helios Informatika Nusantara. This study aims to know and understand the role and strategy of marketing public relations as a business representative in the B2B method. This type of research is descriptive qualitative research with a constructivism paradigm. Regarding the research instruments are interviews, observation, and documentation. The data source for this research uses various documentation owned by the company in conducting online and offline events because these two types of marketing are needed to get leads for the company. Then for data validation, this research uses triangulation. The combined data is seen clearly and in detail regarding the phenomena and problems raised in the study. The results of this study indicate that the marketing strategy used in the B2B method at Helios can run through two stages, digitally and non-digitally, and the various techniques developed within it will support the company sales increase process.

The Effect of Competitive Strategy and Product Quality on Business Performance Study On: Unilever Indonesia Tbk

Currently, in the global market era, many daily necessities are circulating in the world goods market domestic and foreign products. Many companies are developing in Indonesia, both domestic companies and foreign investment companies. One of them is Unilever Indonesia which operates in the primary consumer sector. This research aims to describe efforts to create the influence of competitive strategy and product quality on business performance at Unilever Indonesia Tbk. The urgency of research is to fulfill assignments for the Strategic Management course and as a requirement to take the Final Semester Examination. This research is intended for readers as supporting material for further research in the future and is also useful for writers to develop the process of creating scientific work. This research uses a descriptive quantitative approach method with Explanatory Research research, using annual financial data for the last 3-year period. This method aims to find variable relationships that exist in a community. Using company financial reports to determine the results and influence of competitive strategy and product quality on company sales over several decades and determine the effectiveness of company strategy in the company's business performance. This research was created based on references from several journals by previous researchers with variables that are closely related to the title of the research created by the author.

TIME SERIES FORECASTING MODEL FOR SOLVING COLD START PROBLEM VIA TEMPORAL FUSION TRANSFORMER

Time series forecasting is an important tool in many businesses. It can range from efficiently allocating resources for web traffic, predicting patient needs for staffing requirements, to forecasting a company's product sales. A particular use case, known as "cold start" forecasting, involves making predictions for time series that have little or no historical data, like a new product just entering the retail market. The key assumption of cold start forecasting is that products with similar characteristics should have similar time series trajectories. In such scenarios, traditional forecasting models that heavily rely on past observations may face challenges, necessitating the development of innovative approaches that can effectively make predictions in the absence of a substantial historical dataset. In this paper, Temporal fusion transformer neural network architecture was applied for solving cold start time series forecasting task. Modeling of the method was based on the use of a dataset contained in an open repository. After the preprocessing procedures, the dataset has about 370 time series, each of which has different length of series and has one categorical feature. Categorical feature have only 4 types of different values. For model training was performed to search for optimal hyperparameters across such parameters as: number of attention heads, learning rate, dropout percentage and hidden size.Model performed pretty well on this task. For model comparison were chosen metrics: MAE, RMSE, SMAPE. As can be seen from comparison with such popular models as DeepAR and LSTM, the proposed approach demonstrated the smallest forecasting error. Only one downside is that it can have more problems with anomalies in time series than DeepAR. But at the same time still provide interpretability of results.