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Journal articles on the topic 'Sales analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Varma, Ms D. Bhavya, G. Vijaya Kumari, and R. Vijetha. "Sales Trend Analysis Using ARIMA." International Journal of Research Publication and Reviews 6, no. 4 (2025): 14316–20. https://doi.org/10.55248/gengpi.6.0425.1658.

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2

Pal, Mr Suraj Ramashary, and Dr Ashwini Kshirsagar. "Detailed Study on B2B Sales Analysis." International Journal of Research Publication and Reviews 5, no. 1 (2024): 1901–3. http://dx.doi.org/10.55248/gengpi.5.0124.0231.

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3

Suwandi, S. Sangadji. "Sales Management Analysis and Decision Making." PROCURATIO: Jurnal Manajemen & Bisnis 2, no. 1 (2023): 39–42. https://doi.org/10.5281/zenodo.8207078.

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This comprehensive book aims to provide readers with an in-depth understanding of sales management, covering analysis and decision-making for developing effective sales strategies and tactics. It also delves into various concepts, techniques, and tools used in sales management and how to apply them in practice. The book covers topics such as personal selling, organizational strategies, sales organization structure, salesforce deployment, recruitment and selection, sales training, sales leadership, motivation and reward systems, evaluating organizational effectiveness, and evaluating salesperso

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4

Trivedi, Ishita. "Supermarket Sales Analysis." International Journal for Research in Applied Science and Engineering Technology 8, no. 8 (2020): 797–801. http://dx.doi.org/10.22214/ijraset.2020.30970.

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5

Chitre, Vidya. "Big Mart Sales Analysis." International Journal of Innovative Technology and Exploring Engineering 11, no. 5 (2022): 8–11. http://dx.doi.org/10.35940/ijitee.c9833.0411522.

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In the modern era of reaching new lengths of advancement, every company and enterprise are working on their customer demands as well as their inventory management. The models used by them help them predict future demands by understanding the pattern from old sales records. Lately, everyone is abandoning the traditional prediction models for sales forecasting as it takes a prolonged amount of time to get the expected results. Therefore now the retailers keep track of their sales record in the form of a data set, which comprises price tag, outlet types, outlet location, item visibility, item out

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Vidya, Chitre, Mahishi Shruti, Mhatre Sharvari, and Bhagwat Shreya. "Big Mart Sales Analysis." International Journal of Innovative Technology and Exploring Engineering (IJITEE) 11, no. 5 (2022): 8–11. https://doi.org/10.35940/ijitee.C9833.0411522.

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<strong>Abstract:</strong> In the modern era of reaching new lengths of advancement, every company and enterprise are working on their customer demands as well as their inventory management. The models used by them help them predict future demands by understanding the pattern from old sales records. Lately, everyone is abandoning the traditional prediction models for sales forecasting as it takes a prolonged amount of time to get the expected results. Therefore now the retailers keep track of their sales record in the form of a data set, which comprises price tag, outlet types, outlet location

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7

Jarrett, Jeffrey E. "An Analysis of Lost Sales." Management and Economics Research Journal 01 (2015): 28. http://dx.doi.org/10.18639/merj.2015.01.159412.

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The purpose of this manuscript is to shed light on problems associated with lost sales and the incurring of cost associated with lost sales. An investigation is made to determine if seasonality in sales and lost sales have effects on the efficient operations of supply chains. Optimization is always a goal of management supply chains, but cost increases due to insufficient inventory, low-quality product and the like lead to customers not returning. These are lost sales that occur for many reasons. We study a data set to determine if the ignoring of time series component also has an effect on th

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8

Mr., Chandrashekar P. "Analysis Report on Automobiles Sales." Prajna, UGC Care Listed Journal 4, no. 1 (2023): 88–96. https://doi.org/10.5281/zenodo.12599269.

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This report presents the development and evaluation of a classification model designed to predict the symboling category of vehicles using their attributes and specifications. Symboling is an essential indicator of insurance risk, influencing insurance premiums, safety regulations, and consumer decisions. The model employs a dataset comprising diverse features like normalized losses, make, fuel type, aspiration, body style, and more. The RandomForestClassifier is chosen for prediction, and its performance is assessed through accuracy metrics, confusion matrices, and classification reports. &nb

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9

S. Sangadji, Suwandi. "SALES MANAGEMENT ANALYSIS AND DECISION MAKING." PROCURATIO: Jurnal Manajemen & Bisnis 2, no. 1 (2023): 39–42. http://dx.doi.org/10.62394/projmb.v2i1.57.

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This comprehensive book aims to provide readers with an in-depth understanding of sales management, covering analysis and decision-making for developing effective sales strategies and tactics. It also delves into various concepts, techniques, and tools used in sales management and how to apply them in practice. The book covers topics such as personal selling, organizational strategies, sales organization structure, salesforce deployment, recruitment and selection, sales training, sales leadership, motivation and reward systems, evaluating organizational effectiveness, and evaluating salesperso

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10

Ramdhani, Muchamad Pahmi. "ANALYSIS OF COST OF SALES AND SALES ON NET INCOME." Inovbiz: Jurnal Inovasi Bisnis 9, no. 1 (2021): 133. http://dx.doi.org/10.35314/inovbiz.v9i1.1900.

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This study aims to analyze The cost of sales and sales of net income in retail trading companies listed on the Bursa Efek Indonesia. The population and sample in this study are the financial statements of 12 retail trading companies listed on the Bursa Efek Indonesia for the period 2016-2018. This research technique uses classic assumption test, multiple linear regression analysis, hypothesis test and determination coefficient test. The collection technique uses the documentation and literature review methods. And after the data was collected, the test analysis in this study was carried out wi

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11

Author:, Janine R. Asilo, Mae R. Gulane Tricia, and Bryan Renaissance B. Tormon &. "Sales Management and Profitability among Selected Small Enterprises Renting Commercial Spaces in Panabo City, Philippines." International Journal of Business Management and Technology 6, no. 2 (2023): 281–87. https://doi.org/10.5281/zenodo.7676500.

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The study aimed to determine the level of sales management and profitability among small enterprises renting commercial spaces in Panabo City. As supported by the theory of Wandall and Hoffman (2016), sales operations, sales strategy and sales analysis are the indicators of sales management which can affect the profitability of the business. The researchers employed a survey questionnaire for both variables: sales management and profitability. This study utilizes the descriptive-correlation method with the aid of the adapted survey questionnaire used in gathering the necessary data from the re

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Detering, Nils, Thilo Meyer-Brandis, Konstantinos Panagiotou, and Daniel Ritter. "Suffocating Fire Sales." SIAM Journal on Financial Mathematics 13, no. 1 (2022): 70–108. http://dx.doi.org/10.1137/20m1379800.

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13

Parker, R. Stephen, Charles E. Pettijohn, and Robert H. Luke. "Sales Representatives and Sales Professors: A Comparative Analysis of Sales Training Perceptions, Topics and Pedagogy." Marketing Education Review 6, no. 3 (1996): 41–50. http://dx.doi.org/10.1080/10528008.1996.11488557.

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14

Lauer, Joachim, and Terrence O'Brien. "SALES FORECASTING USING CYCLICAL ANALYSIS." Journal of Business & Industrial Marketing 3, no. 1 (1988): 25–35. http://dx.doi.org/10.1108/eb006048.

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15

Hyland, Andrew, K. Michael Cummings, Eric Nauenberg, Andrew Hyland, K. Michael Cummings, and Eric Nauenberg. "Analysis of Taxable Sales Receipts." Journal of Public Health Management and Practice 5, no. 1 (1999): 14–21. http://dx.doi.org/10.1097/00124784-199901000-00004.

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16

Moriya, Frank E., and John C. Gockley. "Grid analysis for sales supervision." Industrial Marketing Management 14, no. 4 (1985): 235–38. http://dx.doi.org/10.1016/0019-8501(85)90015-x.

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17

Yazhini S, Nogal, Sharath srinivash, Ajay SM, and Mrs Aslam. "Sales Analysis and Prediction System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem43563.

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This dataset contains sales data from various regions, providing insights into the performance of different products over time. The dataset includes the following key fields: Date, which records the transaction date; Product Name, which identifies the sold items; Units Sold, reflecting the volume of each product sold; Revenue, indicating the financial earnings from the sales; and Region, representing the geographic location of the sales. This project involves developing a basic web application utilizing Python for the backend, with Flask or Django as the framework. The frontend is designed usi

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18

Hai, CHEN, CUI Yan - yan, MA li, et al. "Early warning analysis of electricity sales based on multi-factor correlation analysis." E3S Web of Conferences 53 (2018): 02007. http://dx.doi.org/10.1051/e3sconf/20185302007.

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Under the background of the slowdown in macroeconomic growth and the gradual liberalization of the power system reforming market, the competition pressure of power grid companies in the electricity sales market has intensified, and the growth of power sales is not optimistic. It is necessary to conduct research and analysis of electricity sales. This paper conducts the analysis with the following steps: first, determines the leading, coincident, lagging economic indicators based on multi-factor correlation analysis, then synthesizes early warning index, forecasts electricity sales, finally, ac

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19

S, Varshini, and D. Preethi. "An Analysis of Machine Learning Algorithms to Predict Sales." International Journal of Science and Research (IJSR) 11, no. 6 (2022): 462–66. http://dx.doi.org/10.21275/sr22601144946.

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20

P Ingole, Akshay. "Sales Practices in the Machinery Business: A Comprehensive Analysis." International Journal of Science and Research (IJSR) 12, no. 6 (2023): 2374–76. http://dx.doi.org/10.21275/sr23526111256.

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21

D, Dr Kotteswaran, and Pavithra T P. "SALES TREND ANALYSIS SOUTH INDIAN FOOD AND BEVERAGE INDUSTRY." International Journal of Research Publication and Reviews 6, no. 4 (2025): 7766–70. https://doi.org/10.55248/gengpi.6.0425.15195.

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22

Fri Medistya Anke Priyono, Moh Nur Holis,. "SALES SYSTEM ANALYSIS AT UD SAYAN CERAMIC SIDOARJO." Journal of Applied Accounting and Finance Science 4, no. 1 (2022): 23–25. http://dx.doi.org/10.62045/acfis.v4i1.351.

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Sales are transaction activities carried out by two or more parties, sales are also to prepare strategic plans aimed at buyers or consumers to get sales that generate profits, sales are also a source of income for a person or company making sales. buying and selling transactions, in a company the greater the sales, the greater the income generated. The purpose of this research is to find out how the company's sales system performs.The method used in this research is a qualitative descriptive method, which is carried out by collecting related data from the problems encountered and presenting sa

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23

Rohayati, Eti, Martanto, Arif Rinaldi Dikananda, and Dede Rohman. "Sales Data Analysis using Linear Regression Algorithm on Raw Water Sales." Journal of Artificial Intelligence and Engineering Applications (JAIEA) 4, no. 2 (2025): 1054–59. https://doi.org/10.59934/jaiea.v4i2.809.

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This study aims to assess the effectiveness of linear regression algorithm in predicting raw water demand by considering customer transaction data, raw water volume, and seasonal variables. The method used is Knowledge Discovery in Databases (KDD), including data selection, preprocessing, transformation, data mining, and result evaluation. The dataset is divided 80% for training and 20% for testing. The analysis results show that the linear regression model has a coefficient of determination (R²) of 0.77, which means that the model can explain 77% of the data variability. The prediction error

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24

Sahare, Prof Rekha. "Sales Data Analysis Using BI and WEKA." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30123.

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In today's competitive business landscape, organizations rely heavily on data-driven decision-making to gain a competitive edge. Sales data analysis serves as a cornerstone in this endeavor, offering invaluable insights into consumer behavior, market trends, and the overall health of a business. This abstract highlights the significance of sales data analysis and its role in informing strategic business decisions. The abstract begins by outlining the importance of sales data analysis in understanding customer preferences, identifying emerging market trends, and optimizing sales strategies. It

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25

Liu, Dan. "Enterprise Digital Retail Business Data Analysis and Forecasting Based on Time Series Analysis." Advances in Economics, Management and Political Sciences 77, no. 1 (2024): 206–12. http://dx.doi.org/10.54254/2754-1169/77/20241678.

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Digital enterprise management refers to the use of digital technology and information systems to manage various businesses and processes of an enterprise in order to improve its efficiency and competitiveness. Digital enterprise management is crucial to the development and operation of enterprises, which can help them realize more efficient production and management, improve their efficiency and competitiveness, as well as improve their innovation and flexibility, so that they can be more adaptive to market changes and customer needs. This paper focuses on the significance and methods of time

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26

Mohite, Mr Omkar S. "Disease Analysis Using Medicines’ Sales Data." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (2021): 1240–48. http://dx.doi.org/10.22214/ijraset.2021.36405.

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The medical industry is one of the vast organized industries, which deals with various kinds of health-related products and services. Additionally, this industry also contributes in Research and Development of Medicines to cure diseases. Hence, they also have their sales data for a particular area, using some kind of aggregation, predication and clustering we can use the sales, association data for finding the outbreak of a daisies or we can check the sales of that particular area and demand for a particular medicine. Using this data, we can make some precautionary measures on that area plus w

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27

Luthfih, Yussi Dwi, Irena Mei Darnis Halawa, Amelia Agustri Wulandari, and Linawati Linawati. "Analysis of Control Activities in Sales Procedures." ProBisnis : Jurnal Manajemen 14, no. 6 (2023): 792–97. http://dx.doi.org/10.62398/probis.v14i6.434.

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This research aims to find out the application of controls on sales procedures at the Sinar Mulya Agung Building Shop. The research method used is qualitative, and the data collection techniques are interviews and documentation. The results showed that the control over the sales procedure at the Sinar Mulya Agung Building Shop was inadequate, this was because the sales documents used were only sales notes and only signed by the sales clerk, the records used were still simple, and there were no financial reports, there was no separation of functions especially related to sales clerks and respon

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28

A.Madhumidha, Dr T. Ananth Kumar, Dr. P.Kanimozhi, Sunday Adeola AJAGBE, M. Martina Jose Mary, and R. Shyamala Devi. "Automated Real-Time Sales Performance Analysis with Salesforce." Irish Interdisciplinary Journal of Science & Research 09, no. 02 (2025): 20–29. https://doi.org/10.46759/iijsr.2025.9204.

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In the current competitive business world, monitoring and enhancing sales performance is key to organizational growth and sustainability. Based on quantitative analysis, the study explores how Salesforce maximizes sales team productivity by automating mundane tasks and enhancing lead management. Findings indicate impressive gains in core performance indicators such as a 29% decrease in the sales cycle length and 75% decrease in time spent on manual data entry. This study suggests creating a Sales Performance Analysis on Salesforce for improved visibility of sales activity and facilitating data

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29

Ahmad, Nadiah, Nik Kamariah Nik Mat, Muhamad Faiz Mohamed Isa, Sarina Ismail, and Mohammad Harith Amlus. "An Analysis of Alternative Causal Models of Sales Performance on Sales People." American Journal of Economics 2, no. 4 (2012): 101–4. http://dx.doi.org/10.5923/j.economics.20120001.23.

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30

Ravitilova, Ravitilova, Devi Amelia, Ilham Saputra, and Rinda Rinda. "Forecasting Sales: A Comprehensive Analysis of Forecasting Techniques for Sales Budget Determination." Jurnal Audit, Pajak, Akuntansi Publik (AJIB) 2, no. 2 (2023): 97. http://dx.doi.org/10.32897/ajib.2023.2.2.3217.

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This research endeavors to employ sales forecasting techniques on historical sales data for the purpose of determining the sales budget. The application of forecasting is based on sales data from the preceding period, utilizing a descriptive qualitative method. The analysis employs the half-average trend method, generating an estimated sales figure for the upcoming period. This estimate serves as a reference for both inventory planning and the formulation of the sales budget. Within this research, the half-average trend method involves the selection of two X parameter values, namely 0.5 and 0.

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31

G.S., Ramesh, Dr T. V. Rajini Kanth, Vasumathi Dr.D., and G. V. S. Akash Bharadwaj. "Effective Analysis of Sales Data Set Using Advanced Classifier Techniques." Journal of Advanced Research in Dynamical and Control Systems 11, no. 11 (2019): 260–66. http://dx.doi.org/10.5373/jardcs/v11i11/20193195.

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32

Zhang, Anming. "An Analysis of Common Sales Agents." Canadian Journal of Economics 26, no. 1 (1993): 134. http://dx.doi.org/10.2307/135849.

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33

Pataropura, Amesanggeng, Riki Riki, and Ariadi Saputra. "Sales Analysis Using the Forecasting Method." bit-Tech 1, no. 3 (2019): 146–49. http://dx.doi.org/10.32877/bt.v1i3.79.

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Sales Analysis Using Forecasting Method aims to improve effectiveness and efficiency that facilitates companies in business transaction processes, improve the delivery of information quickly, accurately, and transaction data well and minimize errors. The method used in the presentation of this scientific work is by using a forecasting method which helps determine the approximate stock of goods to come. With 3 forecasting modules are: Moving Average, Weighted Moving Average, Trend Projection is used to perform the forecasting process of the upcoming stock of goods. Can solve problems that exist

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34

Tullous, Raydel, and J. Michael Munson. "Organizational Purchasing Analysis for Sales Management." Journal of Personal Selling & Sales Management 12, no. 2 (1992): 15–26. http://dx.doi.org/10.1080/08853134.1992.10753904.

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35

SUBRAMANIAN, KAYALVIZHI. "A Descriptive Analysis on Automobile Sales." Science Proceedings Series 1, no. 2 (2019): 25–27. http://dx.doi.org/10.31580/sps.v1i2.570.

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The automobile market are the fastest developing segment in the planet. India being one of the worthwhile centers for the vehicle advertise which attracts auto majors from everywhere throughout the world. The ongoing development in the passenger car market in India is substantially more than mere market dynamics in a specific vehicle segment. It is a impression of the changing lifestyle of the wealthy class in the nation. This study provides the establishment for governmentâ€™s macroeconomic control and automobile manufacturerâ€™s production.

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36

Rohmawati, Tatik, and Senny Luckyardi. "Analysis of E-Advertising on Sales." Journal of Business and Behavioural Entrepreneurship 5, no. 2 (2022): 1–5. http://dx.doi.org/10.21009/jobbe.005.2.01.

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The purpose of this research is to analyse the increase in product sales using social media advertising. The research was conducted using literature study method and questionnaires that distributed to sellers who used social media advertising in marketing their products. The results show that selling products on social media using advertisements can generate more sales and cunsomers. With social media advertising, sellers can choose the type of potential customers according to the product being sold. The sellers can determine the type of prospective customer based on thier age, residence, and/

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37

Bushardt, Stephen C., Aubrey R. Fowler, and Sukumar Debnath. "Sales Force Motivation: A Theoretical Analysis." Human Relations 41, no. 12 (1988): 901–13. http://dx.doi.org/10.1177/001872678804101202.

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38

Yun, W., and I. Moon. "Warranty Cost Analysis under Continuous Sales." Journal of the Operational Research Society 49, no. 2 (1998): 176. http://dx.doi.org/10.2307/3009984.

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Yun, W., and I. Moon. "Warranty cost analysis under continuous sales." Journal of the Operational Research Society 49, no. 2 (1998): 176–78. http://dx.doi.org/10.1057/palgrave.jors.2600501.

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40

Pragosa, Miguel, and Vitor Basto-Fernandes. "Semantic Integration For Food Sales Analysis." Procedia Technology 5 (2012): 581–88. http://dx.doi.org/10.1016/j.protcy.2012.09.064.

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41

Russo, Joseph A. "Variance Analysis: Evaluating Hotel Room Sales." Cornell Hotel and Restaurant Administration Quarterly 31, no. 4 (1991): 60–65. http://dx.doi.org/10.1177/001088049103100418.

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42

Yun, W., and I. Moon. "Warranty cost analysis under continuous sales." Journal of the Operational Research Society 49, no. 2 (1998): 176–78. http://dx.doi.org/10.1038/sj.jors.2600501.

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43

Griva, Egor, Irina Butorina, Anatoly Sidorov, and Pavel Senchenko. "Analysis and Forecasting of Sales Funnels." Mathematics 11, no. 1 (2022): 105. http://dx.doi.org/10.3390/math11010105.

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This article discusses the use of analysis and forecasting methods for sales funnels to help further decision-making. A number of objective and subjective factors preventing the wide use of various sales funnel forecasting methods are described. It has been substantiated that due to a large number of external and internal factors, perfect forecasting results cannot be obtained. It has been proved that the most accurate and suitable methods for the forecasting of sales funnels are the methods included in the group of time series forecasting methods. Recommendations have been developed to improv

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Pangestuti, Dewi Cahyani, and Raulian Franciskus Pasaribu. "Analysis forecasting sales of tart products." INOVASI 17, no. 4 (2021): 792–801. http://dx.doi.org/10.30872/jinv.v17i4.10180.

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Sales forecasting is an effective and efficient tool for organizations or business people to predict the products that will be produced. Sales forecasting is a method that uses historical data as a reference to get a picture of future value. This research was conducted at the Kuwenak Shop, which produces in the food sector, to be precise, cakes or birthday cakes. On the occasion of this research, there are three forecasting methods used, including moving average, exponential smoothing, and linear trend, taking into account the smallest error rate or error in each method. The linear trend forec

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45

Clampitt, Colleen, and Syed Adeel Ahmed. "ELECTRIC VEHICLE SALES AND INFRASTRUCTURE ANALYSIS." Performance Improvement Journal 61, no. 1 (2022): 10–18. http://dx.doi.org/10.56811/pfi-21-0045.

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ELECTRIC VEHICLES (EV) are a popular choice for many people looking to reduce their carbon footprint, reduce their reliance on oil, avoid fueling stations, or who just want to own the next step in technology. There are questions, however, about how prepared the United States is for an EV owning populace. Before everyone can own an EV, there needs to be enough infrastructure to support the growing numbers of EVs. This paper will examine the current growth of EVs in Louisiana and use that information to determine if Louisiana has enough infrastructure in place to meet the growing demand.

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46

Patel, Paraskumar. "Overcoming Data Gaps in Sales Analysis." Journal of Marketing & Supply Chain Management 1, no. 3 (2022): 1–5. http://dx.doi.org/10.47363/jmscm/2022(1)139.

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In the rapidly evolving global marketplace, businesses face the critical challenge of navigating through extensive sales data to derive actionable insights. This paper explores the complexities of aligning and analyzing sales data from various third-party vendors across different geographies, highlighting the significant impact of data misalignment and gaps on strategic decision-making.

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Wijayanto, Danang Wijayanto, Yohanes Jhony Kurniawan, and Hariyatno Hariyatno Hariyatno. "ANALYSIS OF FACTORS AFFECTING CELLULAR BUSINESS INCOME IN SUKABUMI CITY 2019." Jurnal USAHA 2, no. 1 (2021): 43–57. http://dx.doi.org/10.30998/juuk.v2i1.643.

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This research was conducted to determine the influence of mobile phone sales, sales of credit vouchers and sales of handphone accessories to the revenue of cellular entrepreneurs in the City of Sukabumi. Data collection in research carried out by interview, observation and literature study. Test equipment used with multiple regression analysis, regression coefficient analysis, coefficient of determination with testing partial and simultaneous testing. This study used quantitative research methods aimed at testing predetermined hypotheses. The sample used in this study amounted to 40 respondent

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48

Sang, Yuxin, Peiyan Li, and Ziliang Yin. "Vegetable Merchandise Analysis from a Quarterly Sales Data Perspective." Highlights in Business, Economics and Management 33 (May 9, 2024): 402–9. http://dx.doi.org/10.54097/8e7wb791.

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In the field of fresh vegetable retailing, the category diversity and time-sensitive characteristics of commodities pose unique challenges to inventory management and pricing decisions. Comprehensively analyzing the distribution pattern of sales volume of different categories and individual items of vegetable commodities and their interrelationships is of great significance to retailers' scientific replenishment and pricing decisions. By categorizing vegetable sales every quarter, a comprehensive analysis is carried out on a category and individual item basis. Visualization was used to show th

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49

Forst, Frank G. "Forecasting Restaurant Sales Using Multiple Regression And Box-Jenkins Analysis." Journal of Applied Business Research (JABR) 8, no. 2 (2011): 15. http://dx.doi.org/10.19030/jabr.v8i2.6157.

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Several regression and Box-Jenkins models were used to forecast weekly sales at a small campus restaurant for Years 1 and 2. Forecasted sales were compared with actual sales to select the three most promising forecasting models. These three models were then used to forecast sales for the first 44 weeks of Year 3, and compared against actual sales. The results indicate that a multiple regression model with two predictors, a dummy variable and sales lagged one week, was the best forecasting model considered.

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50

Warsame, Abdisalan Salad. "Factors Influencing Firm Sales Growth: An Instrumental Variable Analysis." International Journal of Marketing Studies 15, no. 2 (2023): 51. http://dx.doi.org/10.5539/ijms.v15n2p51.

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Abstract:

Although several studies have been done on sales growth, the mistake was that firm growth and sales growth were understood as the same thing, using the same perspective and variables for both growth studies. This study takes different perspectives focusing merely on factors influencing sales growth using micro-level data from the World Bank Enterprises Survey (WBES) datasets to examine whether sales growth in sub-Sahara Africa has different stories to tell employing the OLS and 2SLS analyses. Unlike other studies, the results indicated that top management gender diversity has no correlation to

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