Future Sales Research Articles

A Study on Pricing and Replenishment Decision of Vegetables in Fresh Superstores Based on Time Series Analysis

This paper focuses on an in-depth study of the vegetable pricing and replenishment decision problem in fresh produce superstores. Using data preprocessing and multiple mathematical models, the sales and correlation laws between different categories and single products of vegetable products are analyzed. Firstly, the cyclical pattern of sales is revealed through the analysis of historical sales data; secondly, the pricing and replenishment strategies are optimized by using multiple linear regression and time series models; finally, an optimization model is constructed to predict future sales and replenishment, taking into account the spatial limitation of sales.

Pengaruh Biaya Promosi Terhadap Penjualan pada PT Bukit Uluwatu Villa Tbk

This research aims to assess the influence of promotional expenses on sales. The population focus of this study is the quarterly financial reports from PT Bukit Uluwatu Villa Tbk. The analyzed data includes information from the company's financial statements and profit and loss reports. Sample selection was carried out using a non-random (non-probability sampling) approach, applying purposive sampling methods. The sample consists of 35 quarterly financial reports covering the period from 2015 to 2023. The analysis process employed simple regression analysis using the SPSS statistical software. The promotional expense variable is measured by the total promotional expenses, while the sales variable is measured by total sales. This research provides valuable insights for PT Bukit Uluwatu Villa Tbk to optimize their marketing strategies, considering the importance of managing promotional expenses to enhance future sales outcomes. The analysis results indicate a significant influence of the promotional expense variable on sales at PT Bukit Uluwatu Villa Tbk. In other words, promotional expenses play a crucial role in influencing the company's sales performance.

STUDI KELAYAKAN USAHA RUMAH POTONG HEWAN TERNAK DAN UNGGAS PADA ASPEK PEMASARAN

This study aims to determine how the marketing aspects of slaughterhouses based on the amount of livestock and poultry meat consumption on the island of Madura. This research uses a quantitative approach using demand projections to measure products using import data and supply projections used include trend analysis used to project future sales based on previous data and regression analysis used to determine how many people consume livestock and poultry meat. The variables analyzed in feasibility are demand, supply, and the amount of meat consumption per capita. This study uses secondary data obtained by researchers from the Livestock Service Office and the Central Bureau of Statistics. The results showed that by using the trend analysis method, the production in 2023 according to the type of livestock meat was 26 thousand tons and poultry meat was 768 laying hens. Animal consumption on the island of Madura is very low based on correlation analysis of beef 0.165 per capita and layer meat 0.292 this percentage shows a low significance.

“Converging on a new theoretical foundation for selling” five years later: emerging priorities, new applications, & directions for ongoing research

PurposeNot that long ago, half of all sales research was demonstrably if not unequivocally “atheoretical” (Williams and Plouffe, 2007). The foundational argument of this paper is that stronger theoretical development and application of theory in sales research is critical for the sales field to retain its relevancy. The purpose of this paper is to underscore that deliberate and cogent application of HWV (2018) is scant in the recent sales literature (over five years after publication in Journal of Marketing) for one or both of two reasons: scholars either do not understand the paper and/or are fearful of (mis)applying it.Design/methodology/approachMore than simply introducing the articles to this special issue of the European Journal of Marketing (EJM), this paper also makes a number of important, overdue contributions. Although Hartmann, Wieland and Vargo’s JM (HWV, 2018) theoretical and conceptual paper has been well-received by the sales community, it has seen limited meaningful integration or application in sales research since its publication. This paper thus clarifies key misunderstandings and misperceptions with HWV (2018) so that sales researchers can more impactfully apply it to future sales research.FindingsThis paper identifies and then explains key aspects of service-dominant logic (S-D logic) and commonly misapplied and/or misunderstood aspects of HWV (2018) to guide future sales research. Ultimately, the overarching goal of this special issue of EJM is to focus a “spotlight” on sales theory development, while simultaneously demonstrating – through the five articles the special issue reports – that with purposeful effort, rich theoretical insights can effectively be applied to both “classic” and more current and emergent sales research topics.Research limitations/implicationsBecause HWV (2018) draw heavily upon S-D logic, it follows that some aspects of their article have been misinterpreted or misapplied by sales scholars. In particular, the critical concept of “crossing points” (both of the “thick” and “thin” variety) are explicated and detailed further, so as to afford sales researchers with better knowledge and insight on how to apply these key tools within HWV (2018).Practical implicationsThe practical implications of this paper primarily revolve around further educating and clarifying for sales researchers “how” to better apply HWV (2018) to sales research, rather than simply citing it in passing. The paper also concludes by providing a summary and introduction to each of the five EJM special issue articles.Originality/valueThe originality and value of this paper and this special issue of the EJM is twofold. First, both this paper and the entire special issue itself emphasize the ongoing importance of advancing sales research through the meaningful and cogent application of theory. Second, the paper demonstrates that purposeful effort can lead to successful applications of HWV (2018) – as exhibited by the five articles in the EJM special issue – such that rich theoretical insights can be woven into both traditional and contemporary sales research topics.

PELAKSANAAN TRANSAKSI JUAL BELI TANAH DENGAN SISTEM PERANTARA (MAKELAR) BERDASARKAN PERATURAN MENTERI PERDAGANGAN NOMOR 51 TAHUN 2017 TENTANG PERUSAHAAN PERANTARA PERDAGANGAN PROPERTI DI KEC. WATES KULON PROGO

This study aims to know and analyze the process of implementing land sale and purchase using a broker based on the regulation of the minister of trade number 51 of 2017 concerning property trading companies and to find out and analyze the legal responsibilities of the parties if there are legal problems in the future land sale and purchase transaction in Wates sub-district, Kulon Progo Regency. His research methods are empirical juridical based on primary data as well as secondary data. The results showed that based on primary data from interviews with individual brokers in Kulonprogo, it is known that in principle in the process of buying and selling property with the intermediary of brokers, which are individuals or individuals, most of the procedures are almost the same as the processes applied to companies incorporated in the Regulation of the Minister of Trade Number 51 of 2017. It can be seen that the procedure is that the broker generally makes an oral agreement, followed by a written agreement which is generally underhand, providing the choice of location needed by the buyer, verifying data from the landowner to check the authenticity of land ownership; assist the process of transactions with sellers when buyers are interested in buying the desired location; then the broker and seller bring land data to be transacted at the PPAT Notary; Further about the legal responsibility of the parties in the event of legal problems in the land sale and purchase transaction in the future, namely, brokers, and service users should make contracts that affirm the rights and obligations of the parties, in addition to affirming the legal responsibilities that must be borne by the parties in the event of adverse defaults in the future.

The Brand Value of Earnings: An Event Study of Consumer Responses to Earnings Announcements

ABSTRACT We provide evidence from the first short-window event study of consumers’ perceptual responses to earnings announcements using daily consumer perception data. We document a positive association between the change in consumers’ overall perceptions of a brand at the time of the earnings announcement and the earnings surprise—that is, a positive consumer earnings response coefficient (CERC). CERC is larger when there is greater traditional news or social media activity, indicating that news dissemination is an important channel for consumers to respond to earnings news. Moreover, CERC varies based on brand and consumer characteristics. Changes in consumer perceptions at the time of the earnings announcement are positively associated with changes in purchase consideration and intent and with changes in realized future sales growth. To maximize identification, we document a positive and statistically significant CERC in a controlled experiment. Our findings demonstrate the importance of earnings to an important stakeholder. Data Availability: Data are available from the sources cited in the text. JEL Classifications: M31; M41; G14.

The Ordered Weighted Average Sector Liquid Return Index: A Method for Determining Financial Recovery from Sectoral Debt

The primary aim of this article is to demonstrate that using the average of ratios as a representative value for measuring the health of a sector does not constitute a valid procedure. After mathematically demonstrating this objective, the article will then focus on introducing a new index for estimating the potential debt return value for a sector or group of companies. Next, the article details the start of the process for creating a new index to improve investors’ understanding of the risk associated with a sector or a group of companies meeting short-term obligations based on assigned probabilities of future sales. Given that said value is intended to represent an indicator of expected liquid solvency, its construction will take treasury tensions into account. An Ordered Weighted Average type of aggregation function is used to aggregate the magnitudes in this scenario. Consequently, the second objective of the present work is the creation of this index, which provides an initial estimate of how much money can be recovered from a sector’s debt.

Sales Predictor Using Simple Linear Regression and Simple Moving Average Model

Abstract: In the rapidly evolving business landscape, the accurate prediction of sales trends holds paramount importance for informed decision-making. Our project deals with the application of two fundamental forecasting models: SLR and SMA Models to predict future sales trajectories. The Simple Linear Average model involves the computation of a basic mean sales value, while the Simple Moving Average model incorporates a rolling average over a predefined time span. Upon successful training of the model, the model can predict the sales of the particular product with accuracy above 90%

Smart Cars – Predicting Future Customers

This document gives Smart cars which are also known as autonomous cars or self-driving cars which moves with little or no human input. They are efficient and avoid accidents so many car manufacturing companies have started working on these autonomous cars and for this process they are investing huge money in R&D for best and efficient cars. But the main issue is as they are investing more money they are expecting to get huge profits, so we came up with a solution. In this paper we will set up a machine learning model which will predict the future sales or customers buying these car sand this will increase the income for the companies. So as to achieve this predictive model, we will make use of frame works and libraries of python.

Co-Opetition and the Firm’s Information Environment

Some firms in the technology sector choose to cooperate with competitors (“co-opetition”) in standard setting organizations (SSOs). These SSOs create technology standards that facilitate rapid market penetration of new technologies such as Wi-Fi, Bluetooth, and 4G. Active participation in the standard setting process requires the exchange of proprietary information with competitors. Although the goal of such information sharing is to further a technology or a product market, firms potentially receive an additional benefit from access to competitor and industry information. We examine whether contributing to SSO committees enhances a firm’s information set and allows managers to better predict future sales. We find that the centrality of a firm’s location within the network of SSO collaborators is positively related to the accuracy of the firm’s sales forecasts. This relation is stronger when firms exchange more information with direct competitors and with larger firms, when forecasting is more difficult ex ante, and when firms forecast over longer horizons. Our findings show that collaborating with competitors in the product market provides an important additional benefit of improving the manager’s information set. This paper was accepted by David Simchi-Levi, accounting. Funding: This work was supported by the Wharton School, Institut Européen d’Administration des Affaires, the Institut Européen d’Administration des Affaires-Wharton Alliance, and the Mack Institute for Innovation Management. Supplemental Material: The data and online appendix are available at https://doi.org/10.1287/mnsc.2021.03152 .

Pelatihan Teknik Proyeksi Bisnis Pada Kelompok Usaha Batu Bata Di Kelurahan Limbung Kecamatan Bajeng Kabupaten Gowa

Community Service Partners (PKM) is a micro and small brick business. Knowledge of business projections among business owners in Batu Bata is still very limited. The aim of this service is to empower traditional business owners with the knowledge and skills to produce accurate business projections to assist in developing their business. The implementation method uses lecture, exercise, and discussion/question and answer methods. The participants were brick business owners from the Limbung village, Bajeng District, Gowa Regency. The technique for implementing this activity includes three stages starting from the preparation stage, implementation stage and activity evaluation stage. The results of the training show that traditional business owners experience difficulties in applying business forecasting techniques to their businesses because sales records are sometimes incomplete or non-existent. After carrying out the simulation, participants can understand the basis of sales forecasts for future sales forecasts. Additionally, brick-and-mortar business owners can know the exact estimates of their business. Knowledge of business forecasting is expected to improve business performance and competitiveness. The limitation of this training is that the implementation method does not use instructional techniques so that knowledge about business forecasting can be implemented in business activities.

Multiple directorships of outside directors and firms’ cost behaviour: evidence from Korea

ABSTRACT This study examines how multiple directorships of outside directors are related to firms’ cost behaviour. Results based on a sample of Korean-listed companies from 2011 to 2017 show that the level of cost stickiness is attenuated when outside directors hold multiple directorships. However, multiple directorships do not mitigate the degree of cost stickiness that is associated with managers’ strategic response to expected future sales increase. We find evidence that the degree of cost stickiness of firms with high cash holdings can be attenuated by multiple directorships. These results suggest that outside directors who serve on multiple boards are effective at monitoring cost management of empire-building managers. Further, the level of cost stickiness is not attenuated by outside directors sitting on the boards of multiple subsidiaries within the same business group. These results suggest that outside directors’ business group affiliations undermine their monitoring roles as independent directors. This study is closely related to finance and accounting literature on economic benefits of multiple directorships or board connection. HIGHLIGHTS The level of cost stickiness is negatively associated with multiple directorships of outside directors. -Outside directors holding multiple directorships are effective at monitoring cost decisions. -Outside directors' business group affiliations undermine their monitoring roles.

Consumer Behavior Analysis and Marketing Strategy Optimization in the Chinese Live Action Role Playing Market

In 2016, a new variety show Whos the Murder appeared, bringing a new form of entertainment: Live Action Role Playing (LARP) game. In 2018-2019, offline LARPs appeared, soon becoming the most popular entertainment method for the Z generation. The paper focuses on the consumers of the LARP market, analyzing their consumption behavior preferences and determining the driving factors of LARP consumption behavior based on existing consumption data. Using the analytical results, the paper can predict the sales of new scripts and help LARP merchants optimize their marketing strategies. The article mainly uses descriptive and predictive analysis (regression model) to study LARPs consumption data collected from the LARP website. The paper finds that difficulty level, duration time, and issue type (price) have a significant influence on consumer behaviors. Also, the paper generates a model for future sales prediction.

SUPERMARKET SALES PREDICTION USING MACHINE LEARNING

The huge supermarkets are more data-driven in todays retail world. These businesses tediously analyze sales data for each individual item they provide in order to optimize inventory management and predict managers demand. Using machine learning techniques, anomalies and patterns are being added to the data repository. This data is used to forecast future sales volume, which is critical for merchants like supermarkets. We provide a prediction model, similar to supermarkets, that uses the capabilities of the XGBoost algorithm to forecast a companys sales. Our findings show that our suggested model exceeds existing models in terms of predicted accuracy, illustrating the power of complicated machine learning approaches in optimizing retail operations. This study provides useful information for improving sales forecasting and inventory management. KEY WORDS: Regression, Sales, Prediction, Data Exploration, Supermarkets, XGBoost.

A new rolling forecasting framework using Microsoft Power BI for data visualization: A case study in a pharmaceutical industry

Demand forecasting is a vital step for production planning and consequently, for supply chain efficiency, especially for the pharmaceutical (pharma) supply chain due to its unique characteristics. Numerous models and techniques that are proposed in the literature but little in concrete and generic framework to forecasting process, mainly for pharmaceutical supply chain. Unlike studies in the literature, this study not only perfectly predict the sales of a pharma manufacturer, but also visualize the results via a developed dashboard using modern information technology and business intelligence. In this research, a rolling forecasting framework comprising of different steps and specialized tools is proposed that can assist supply chain managers to perform an accurate sales forecasting and consequently a better performance and specifically patient satisfaction. The proposed generic framework combines the use of Visual studio C++ software to extract optimal forecasting and the Power BI software to monitor the accuracy of the obtained sales forecasts. Three exponential smoothing methods are integrated in the proposed framework, which is open to adding more new forecasting methods. The proposed framework is tested for many data sets from a pharmaceutical manufacturer company, and the results obtained show superior performance, especially a clear decline in both forecast errors, which can reach 75% and a drop of stock level to 50%. Therefore, the company is currently using it and a future integration with their ERP is being carried out. The proposed rolling forecasting framework contributes to insightful decision-making through the visualization of accurate future sales and turnover, and consequently, an efficient stock management and effective production planning.

Is the Net Promoter Score a Good Predictor of Future Sales Growth? : A Comparative Study with the Customer Satisfaction Index

Is the Net Promoter Score a Good Predictor of Future Sales Growth? : A Comparative Study with the Customer Satisfaction Index

An Analysis about the Pure Electric Vehicle Sales Prediction Based on the BP Neural Network

With the increasing demand for pure electric vehicles among Chinese residents, being able to accurately forecast the future sales volume of pure electric vehicles has become a hot topic of research in today’s society. In this paper, the sales volume of pure electric vehicles from January 2020 to December 2021 have been collected. And based on the monthly sales volume of 24 months, the BP neural network model has been used to test the data, and the sales volume of pure electric vehicles from January to December 2021 has been predicted with the trained model. Comparing its prediction results with the actual sales volume, it has been found that the BP neural network model can predict the future sales volume of electric vehicles well; and based on the prediction results, it can provide some useful references for the production planning and the raw material procurement.

Jenis dan Klasifikasi Penjualan dalam Ekonomi Syariah

Islamic economics has different principles from conventional economics, including in terms of sales contracts. In Islamic economics, there are several types of sales contracts used, such as bai' al-salam (future sales) and bai’ al-salam(manufacturing sales). Trust sales contracts are also important in ensuring transparency of the price of the goods or services sold. The research method uses descriptive qualitative in describing and explaining specifically with literature studies in data collection. The purpose of this research is to find out specifically about the types and qualifications of sharia sales that do not contain gharar and usury. In Islamic economics, payments in sales contracts can be deferred or paid in installments without involving interest or riba. This allows the buyer to pay according to an agreed schedule. Sales contracts in the Islamic economy differ from interest-bearing loan contracts, where there is an exchange of goods or services at a predetermined price. Islamic banks use sales contracts as a legitimate alternative to interest-bearing loan contracts, allowing them to provide financing that is fair and compliant with sharia principles. In the Islamic economy, there are also contracts for the sale of future commodities (salam), the sale of manufacturing (istisna'), and currency exchange (sarf). Islamic banks have an important role to play in facilitating these sales contracts, as intermediaries who ensure the contracts adhere to Shariah principles and meet applicable legal requirements. With a good understanding of the different types of these sales contracts, economic actors can choose the ones that suit their needs while complying with sharia principles.

Finance, informal competition, and expectations: A firm-level analysis

This paper documents the link between finance and informal competition. Using longitudinal firm-level data, we show that formal firms that are more exposed to the competition of informal firms are less likely to apply for a bank loan. This result is not due to sample selection, omitted variable bias, or reverse causality, and it is robust to different econometric specifications, including the use of an IV strategy. As for the mechanism explaining our result, we show that firms more exposed to informal competition have worse expectations on future sales growth, which in turn are associated with a lower probability of loan application. Finally, we provide suggestive evidence excluding supply-side mechanisms that may explain heterogeneities in firms’ access to finance.

Estimation of Sales Decline Risk Based on COVID-19 as a Model

Owing to the coronavirus disease 2019 (COVID-19), many companies experienced a sharp and significant decline in sales, resulting in a major crisis. This study proposes a method for estimating the risk of a sudden and significant decline in sales to tackle the aforementioned issue. The method is based on the distributional characteristics calculated from historical data of companies mainly in the transportation industry, which are vulnerable to disasters, using the damage caused by COVID-19 as a lesson. Furthermore, we conduct an empirical analysis using the proposed stochastic model for the case of the All Nippon Airways Co., Ltd. (ANA), a major Japanese airline company. The results are as follows: (1) the sales change rates are normally distributed before COVID-19, but inclusion of post-COVID-19 data produced asymmetric distribution of sales change rates; (2) the proposed statistic is log-normally distributed (including post-COVID-19 data) for a time interval of two or three years; (3) the probability of actual sales decline was estimated to be between 0.1% and 1.6% in fiscal year (FY) 2020 and FY2021 post-COVID-19; (4) the estimated risk of future sales decline is well-grounded in light of past actual values.