Purchase Volume Research Articles

Informed trading of out‐of‐the‐money options and market efficiency

AbstractWe examine the stock return predictability of out‐of‐the‐money (OTM) put‐to‐call trading volume ratio (OTMPC). Our numerical analysis predicts that in the US equity option market, informed investors rarely write OTM options because the leverage effect is not sufficient to compensate for transaction costs. OTMPC thus captures the informed investors’ OTM put purchase volume relative to their OTM call purchase volume. After controlling for existing empirical proxies for informed option trading, we find that OTMPC predicts future stock returns and corporate news. The return predictability offers implementable stock portfolio strategies. Our findings suggest that market inefficiency can emerge from uninformed investors’ limited knowledge about how transaction costs influence the trading strategies of informed investors.

Joint decision on wooden pallet lease pricing and purchase volume under recycling and reusing mode in the Chinese market

A closed-loop wooden pallet rental system was considered in this study, which involved a wooden pallet manufacturer, a wooden pallet leasing company, and several customers. To solve the joint optimization problem of pallet lease pricing and purchase volume under recycling and reusing mode, a mathematical model was constructed with the objective of maximizing the profit of pallet renters under deterministic and stochastic market demand. Meanwhile, comparative analyses were conducted on the optimal pricing, optimal order quantity, and expected profit under the two leasing modes of considering and not considering maintenance. On this basis, sensitivity analyses were performed on some parameters of the two modes. Results showed that pallet renters can adopt the maintenance strategy to increase profits by lowering the rental price appropriately regardless of the market demand. The wood pallet rental supply chain can be more efficient when the pallet residual value, recovery integrity rate, and utilization rate are higher and the out of stock cost and inventory holding cost are lower. Under the maintenance mode, a lower repairing price and higher reparability rate resulted in a more favorable maintenance mode.

Prediction of Purchase Volume of Cross-Border e-Commerce Platform Based on BP Neural Network

As a new form of foreign trade, cross-border e-commerce has huge development potential. Although the development prospect of cross-border e-commerce is good, the management of global supply chain is very important in order to gain a place in the fierce competition and develop steadily. The traditional forecasting of purchasing volume adopts time series, and the forecasting model is relatively simple. The purchase volume of the platform is related to the various consumption behaviors of consumers, such as the number of product reviews, the number of product collections, and whether there are tax subsidies. The sales volume in the next few days is predicted by the item number, time, and sales quantity. The four-layer BP neural network model is used, and the MATLAB neural network toolbox is used to draw the training error curve and the correlation coefficient curve. After network training, the training correlation coefficient R reaches 95.823%, and the prediction accuracy obtained at this time is higher. Further, using the established model based on BP algorithm, the traditional BP algorithm is optimized to obtain the purchase quantity of commodities. The method is applied to the forecast of commodity purchase volume of a cross-border e-commerce platform, and the results show that the average error rate of this method is 5.9%, which has high practical application value. The research results show that this paper considers multiple influencing factors and selects an appropriate forecasting method, which can effectively improve the accuracy of the company's commodity sales forecast, so as to better formulate procurement plans and optimize inventory structure, which has certain implications for the actual operation of cross-border e-commerce platforms.

Internal Debt Options during the Two Double Shocks and Its Impact on Foreign Reserve in Iraq

The research aims at a statement Internal Debt options during shocks and the impact of this borrowing in the volume of the foreign reserve, using induction and deduction with available data analysis. During the period (2004-2013) did not require the use of borrowing across (financial institutions, discounted transfers, bonds); it was only sufficient by transfer with commercial banks that can finance of temporary budget deficits: rose and decline of volume of foreign reserve according to the changes of oil prices and the volume of purchases and sales of the Central Bank of Iraq. Central Bank of Iraq (CBI) has significantly contributed to Internal Debt through bond and discounted transfers in the secondary market; thus, funding the public budget and sustaining the momentum of battles during the first double shock (2014-2017), which reflected how it is negatively affected the volume of foreign reserve, in other words, reduction the proportion of foreign assets to local assets. The second double crisis (2020) reduced the exchange rate of the Iraqi dinar against the US dollar, which was reflected at high prices; inflation reached (5.6) at the end of the first half of 2020, which means adopting a new choice to finance the budget deficit. This means that there is an inverse relationship between the volume of foreign reserve and internal debt, where decrease volume of foreign reserve during two double shocks

The coronavirus’s effect on the decisions and habits of food purchases in Hungary

This article was inspired by current events. The shopping craze generated by the coronavirus pandemic raised some questions that this article aims to answer by analysing a variety of suppositions. The coronavirus pandemic caused panic shopping amongst consumers, whose motivation for increasing the volumes of shopping revolved around ensuring a safety margin of groceries while also reducing the number of shopping trips. The consumers did most of their shopping in hyper, and supermarkets, as well as in bigger ABCs and grocery stores (Lidl), where there’s a wider range of products and larger stock. The average consumer bought much more than the basic groceries during this period. Our research started in March 2020 and ended in May 2020. To validate our assumptions, primary information is derived from the statistical processing of a large number of data from a representative questionnaire survey of 724 respondents. The results show that for many people this period was about stockpiling storages of groceries. Flour saw the biggest increase in purchase volumes, but chicken and pastas were also amongst the more popular items. Stores with the biggest range of selection were able to satisfy this demand. As evidenced by data, consumers also purchased items, which are needed for any household during an emergency and are easy to store in higher volumes. These items include different oils and fats, which are required for cooking, and non-perishables, such as salamis, canned foods, rice and mineral water.

Deep Learning Based Purchase Forecasting for Food Producer-Retailer Team Merchandising

Expired foods turning into waste has always been an important issue. In Taiwan, more than 36,000 metric tons of unopened expired food, worth more than $130 million, are thrown away from retail stores as waste each year. Insufficient inventory results in the loss of business prospects for retailers, whilst excessive inventory results in abandoned merchandise. Foods with a short shelf life are particularly vulnerable. Typically, food producer and retailer would form team merchandising (MD). The team MD mechanism is responsible for ensuring safety and quality, not for forecasting demand. This study uses artificial neural networks (ANNs) to analyze sales data to forecasting purchase volume in response to changes in store environment, weather, events, and consumer attributes. The study object is a sort of cream puff with a short shelf life cobranded by a retailer. According to the experimental results, the adopted proposed model in this study effectively reduces the error in purchasing; the mean-square percentage error (MSPE) of the forecast values is less than 6%. The importance of this study is on promoting the team MD’s green energy management capabilities in food production and verifiably achieving the goal of environmental sustainability.

Application of Data Mining Methods in Grouping Agricultural Product Customers

The sheer complexity of the factors influencing decision-making has required organizations to use a tool to understand the relationships between data and make various appropriate decisions based on the information obtained. On the other hand, agricultural products need proper planning and decision-making, like any country’s economic pillars. This is while the segmentation of customers and the analysis of their behavior in the manufacturing and distribution industries are of particular importance due to the targeted marketing activities and effective communication with customers. Customer segmentation is done using data mining techniques based on the variables of purchase volume, repeat purchase, and purchase value. This article deals with the grouping of agricultural product customers. Based on this, the K-means clustering method is used based on the Davies–Bouldin index. The results show that grouping customers into three clusters can increase their purchase value and customer lifespan.

Testing the Insider Trading Anomaly in FTSE-350.

In recent studies, numerous anomalies against the weak and semi-strong-forms of efficient market hypothesis (EMH) have been found insignificant after controlling the small-firm effect. We investigate whether the insider trading anomaly, a major anomaly against the strong-form of EMH, can survive after excluding small firms with a novel data set (FTSE-350) and document several new findings. We find a substantially larger number of insider purchases than sales, while the average volume of insider sales is much higher than the average volume of insider purchases. Echoing recent US studies, we find that insider sales generate more abnormal returns than insider purchases do. We find much lower abnormal returns from insider trading than documented in the literature and the associated trading costs, which suggests that the market efficiency of individual stocks may depend on their sizes, and even the strong-form of EMH holds to a larger extent than previously recognized.

The impact of National Centralised Drug Procurement policy on the use of policy-related original and generic drugs in China.

To evaluate the effects of the first round of National Centralised Drug Procurement pilot (so-called '4+7' policy) on the use of policy-related original and generic drugs. This study used drug purchasing order data from the Centralised Drug Procurement Survey in Shenzhen 2019, covering 24months from January 2018 to December 2019. '4+7' policy-related drugs were selected as study samples, including 25 drugs in the '4+7' procurement list and 69 alternative drugs that have an alternative relationship with '4+7' List drugs in clinical use. '4+7' List drugs were then divided into bid-winning and bid-non-winning products according to the bidding results. Included drugs were sorted into original and generic drugs. Purchase volume, expenditures, and daily costs were selected as outcome variables, and were measured using Defined Daily Doses (DDDs), Chinese Yuan (CNY), and Defined Daily Drug cost (DDDc). A single-group Interrupted Time Series analysis was adopted to quantify policy effect. After policy intervention, the overall policy-related original drugs significantly decreased by 0.39 CNY (95% CI: -0.62 to -0.17, p<0.01) in DDDc, 5949.36 thousand DDDs (95% CI: -8276.67 to -3622.05, p<0.001) in volume, and 31,575.08 thousand CNY (95% CI: -41,812.68 to -21,337.49, p<0.001) in expenditures. The volume proportion of generic drugs increased from 78.6% to 91.0%, and the expenditure proportion of increased from 30.9% to 49.8%. '4+7' policy promoted the substitution use of domestic generics against original branded drugs and played positive effects on drug price cut and medication burden reduction. The proportion of original branded drugs and generics that passed generic consistency evaluation significantly increased after policy intervention, indicating the improvement of the overall quality level of drug use in China.

Change in Consumer Behavior Due to Covid Crisis: An Exploratory Study

The purpose of the study was to explore consumer behavior (purchase pattern, volume, and frequency), and household expenditure alteration due to the COVID crisis. Furthermore, to study the perpetuity of those changes. Researchers used a mixed-method approach based on qualitative interviews, secondary data, and media analysis, that is, using a qualitative, exploratory research design. Data were collected through Reflective Journal Logs, 34 in-depth interviews, extensive literature review of secondary sources, and netnography. The study was cross-sectional and applied in nature. Researchers divided the respondents based on income to explore the impact of income. Data reduction, analysis, and interpretation were made manually, and the overall method used was narrative qualitative research. Researchers found the consumer’s purchase patterns of products and services in this study. Some new habits were also found towards purchase behavior, expenditures, and savings. Researchers also found the perceptions towards perpetuity of those changes and the impact of income on all those changes. Many researchers conducted studies on this subject, but no significant research from the micro, that is, household perspective, was found. Besides, the factors such as perceptions towards the perpetuity of the changes were missing, especially from the problem’s qualitative aspects. This study will help marketers identify new demands and use them for better customer service, leading to a strengthened relationship with them and profit for the organization.

DETERMINANTS OF COMPETITIVENESS OF DAIRY ENTERPRISES ON THE EXAMPLE OF THE WIELKOPOLSKA REGION

The aim of the article is to determine the competitive potential of selected dairy enterprises located in the Wielkopolska Region and establish the determinants of competitiveness of the researched entities. The selection of the research sample was purposive and was determined by two assumptions. First of all, the Wielkopolska Region, according to the data of the Central Statistical Office, takes third place in terms of milk production in Poland, where the cooperative character of milk processing prevails. This region has the largest number of dairy cooperatives, i.e., 26 cooperative dairy plants operated in 2019, constituting a share, in the whole industry, at a level of 16%. Secondly, for empirical research, only district dairy cooperatives located in the Wielkopolska Region were selected, which, since 2007 to 2019, submitted their financial statements to the Emerging Markets Information Service (EMIS) database, conducted business activities and were engaged in milk processing and the production of dairy products. At the end of 2019, there were fifteen entities that met the above criteria, and this group was selected for further empirical analysis. The conducted research shows that dairy cooperatives, having short term financial liabilities and an average income from sales, have the best competitive potential. The weakest competitive potential was achieved by cooperatives with long-term financial liabilities and a low profitability of sales of offered products. The evaluation of competitive potential showed that the direction of influence of evaluated elements of competitive potential was not clearly defined. It means that we should think over the construction of the synthetic measure for the evaluation of the competitive potential of dairy enterprises, which, apart from the financial condition, will consider other areas i.e., the production potential, investment outlays borne by an enterprise for modernization, the purchase volume of milk and the number of suppliers cooperating with a given enterprise.

Households Under Economic Change: How Micro- and Macroeconomic Conditions Shape Grocery Shopping Behavior

Economic conditions may significantly affect households’ shopping behavior and, by extension, retailers’ and manufacturers’ firm performance. By explicitly distinguishing between two basic types of economic conditions—micro conditions, in terms of households’ personal income, and macro conditions, in terms of the business cycle—this study analyzes how households adjust their grocery shopping behavior. The authors observe more than 5,000 households over eight years and analyze shopping outcomes in terms of what, where, and how much they shop and spend. Results show that micro and macro conditions substantially influence shopping outcomes, but in very different ways. Microeconomic changes lead households to adjust primarily their overall purchase volume—that is, after losing income, households buy fewer products and spend less in total. In contrast, macroeconomic changes cause pronounced structural shifts in households’ shopping basket allocation and spending behavior. Specifically, during contractions, households shift purchases toward private labels while also buying and consequently spending more than during expansions. During expansions, however, households increasingly purchase national brands but keep their total spending constant. The authors discuss psychological and sociological mechanisms that can explain the differential effects of micro and macro conditions on shopping behavior and develop important diagnostic and normative implications for retailers and manufacturers.

Державні публічні закупівлі легкових автомобілів в Україні

The article presents the most popular models of passenger cars among authorities, institutions and organizations. The author provides information on the volume of purchases and total costs of cars of different brands and autobody types by authorities, institutions and organizations from January to October 2022. It is found that the largest number of passenger cars was purchased by law enforcement agencies, health care institutions, housing and communal services enterprises, and the State administration bodies. The most popular models were Renault Duster, Renault Express, Toyota RAV4, Renault Sandero Stepway Life+, Haval Jolion. The most popular were: among crossovers – the Renault Duster, among sedans – Peugeot 301, among the SUV – Toyota RAV4, among the hatchbacks – Renault Sandero Stepway Life+, among the station-wagons – ?koda Superb and Renaut Megan, among the vans – Fiat Doblo Combi Mahi, among the minivans – Renault Express, among the minibuses – Mercedes-Benz sprinter 313. Renault cars are most demanded. The most popular autobody types are crossover, hatchback and SUV. Sedans are popular in law enforcement agencies, health care facilities, housing and communal services. Crossovers are most in demand in law enforcement agencies, health care institutions, and the State administrations. Hatchbacks are in demand in law enforcement and healthcare facilities. The SUVs are of greatest popularity in law enforcement agencies, housing and communal services enterprises, and the State administrations. The main buyer of the vans are the State administrations, health care institutions, and housing and communal services enterprises. Minivans are used by law enforcement agencies and housing and communal services enterprises. The author estimates that in 2022, through the Prozorro public procurement website, government agencies spent UAH 234.003 million on the purchase of passenger cars.

Determination of parameters for the formation process of rare events in the economy for their subsequent forecasting

The article presents a method for determining unknown parameters of the process that forms rare events in the economy.The idea behind the study of rare events in economy is to consider these events not just from a statistical point of view, but from the point of view of the processes that form these events, moreover, as well as a process can be an arbitrary algorithm. Such an event generation process will use parameters, which can be static or dynamic. For example, if we consider the consumption process, which forms discrete purchases of an uncontrolled customer, then such parameters can be the maximum stock and a dynamically changing consumption rate. In general, the process can be arbitrary and possess various parameters. The task is to determine these parameters of an unknown process obtaining only a sample of rare events. The idea of the method is to minimize the loss function, which is determined based on the differences between the events generated during the operation of the process and events from the initial sample of observations. Each event, in addition to the time of occurrence, is also characterized by additional information, for example, the purchase volume. We are trying to find out such parameters of such a process that would allow us to get a very similar sample of events. The dynamic parameters of the process are set in the form of cubic splines of a special structure. For an unambiguous determination of each dynamic parameter, a roughness penalty of the corresponding splines is introduced into the objective function. An example of a process and its structure of parameters to be determined is shown. Optimization is performed numerically, based on the Nelder–Mead algorithm, which runs on a grid to determine the global optimum. The process parameters are determined in steps, at the beginning just to get a few events, then the next events. That allows one large optimization task to be divided into a sequence of simple tasks, this significantly reduces the overall complexity. An assumption is described that must be fulfilled for such a technique to be valid. An example of determining unknown parameters is considered on the example of the consumption process. After determining the process parameters, one can proceed to extrapolation of parameters and forecast future events.

ПОТРЕБИТЕЛЬСКОЕ ПОВЕДЕНИЕ В УСЛОВИЯХ ЦИФРОВИЗАЦИИ В ЭКОНОМИКЕ

The article examines the structure of modern consumer behavior in the context of digitalization of trade. An important consequence of the development of Internet technologies is the digitalization of society, as well as the virtualization of various aspects of economic relations. These aspects include not only the digitalization of money, but also the digitization of markets for goods and services. The paper analyzes statistical data on sales on the Internet, as well as on the dynamics of the growth of the online shopping market in Russia and the world as a whole. Trends in the structure of the use of Internet services are revealed. Analysis of the Internet traffic of Russian citizens revealed an increase in its use as a means of ordering goods and services. There was a pronounced increase in the volume of online purchases, in particular, since 2017, there has been an increase in the number of orders on the Internet in Russia, but more than half of the country's population does not use the Internet to make purchases. The assessment of the behavior of modern consumers is given. The reasons that can influence consumers when choosing a shopping method are identified. The analysis of the terms of transactions in the digital space revealed differences and similarities with the classical theory of economic behavior. Due to psychological aspects, the use of funds on the Internet increases the expenses of the population. Using the example of the use of Internet sites and services, a brief justification of current trends in behavioral economics is given. Various techniques and methods of sales promotion on the Internet are described. Parallels are drawn between the techniques of offline and online stores to attract the attention of customers. The shares of Internet commerce in the GDP of various countries are considered. The advantages and disadvantages of digital and direct trading are revealed. There is a difference in the number of competitors in both cases. Psychological factors affecting the attitude of consumers to sellers are described. With the continuing trend, the modern Russian economy is striving for full digitalization. The use of new Internet technologies has led to a change in the format of interaction between sellers and buyers.

Performance of Food Distribution Institutions in Realizing Price Stability and Access to Rice Food at The Household Level of Farming Group in Bantaeng Regency

This study aims to determine the performance of inputs, outputs, benefits, and impacts of Strengthening Community Food Distribution Institutions at the Food Security Agency in Supporting Grain Price Stability and Rice Food Access at the Household Level of Farmer Groups Bantaeng Regency. The type of research used is qualitative research. Informants in this study were the Head of Agency, Head of Division, Head of Regency Development Team, Field Extension Officer, and Head of Farmer Group. Based on these needs, organizational or program objectives are drawn up. The organization or program provides inputs (staff, buildings, sources of funds), arranges activities (activities) to process these inputs in a specific process to become outputs, turn them into benefits, and take the form of impact performance. The results showed that from the aspect of input performance, namely the availability of business capital and building capital for warehouses, the team of coaches and extension workers. Aspects of Output Performance, the form of business capital is greater than the initial capital, the price of grain increases, and the volume of grain purchases increases. Benefit Performance Aspect, namely the greater use of the Social Assistance Fund, as seen from the gains achieved, the price of grain during the harvest season is under control because it follows the government benchmark price (HPP).

A impulsividade afeta a tomada de decisão em compras on-line?

Impulsivity can be defined as a comprehensive construct that encompasses characteristics such as action without prior conscious judgment, action with less prudence, risk taking and quick decision. It is a complex phenomenon and can be characterized as a set of cognitive and behavioral patterns that lead to short, medium and long-term losses and can be presented in four distinct constructs, namely: urgency; lack of forethought; lack of persistence and sensation-seeking. With the advancement of technology and access to virtual environments, companies are developing tools to engage consumers and create behavioral strategies that influence decision-making at the time of purchase. The research focuses on understanding how impulsiveness is related to decision making regarding consumption. The objective is to analyze the correlations between individuals with the highest impulsivity score and the number of online purchases according to the four impulsivity constructs, to verify how the low or high price of goods affects the volume of online purchases and whether gender and socioeconomic characteristics interfere in the consumption/impulsivity relationship. The research is cross-sectional, exploratory, consisting of the investigation and analysis of data collected with a sample of 500 participants, neurotypical in the age group of 18-59 years. It will be carried out via an online platform, the following instruments will be used: Impulsive Behavior Scale (UPPS-P), Social Desirability Scale; Socioeconomic Questionnaire; Self-Report Inventory for Adults - 18/59 years old (ASR - 18/59 years old); and the Consumption Questionnaire that will be prepared for this research and then submitted to 6 expert judges with a degree of agreement of ≥80%, to verify: accuracy, sensitivity and specificity in measuring the behavior of compulsive consumption compared to questions of impulsivity and the relationships between sex and income characteristics in impulsive consumption behaviors.

КОМПЛЕКСНЫЙ АНАЛИЗ И ОЦЕНКА ЭФФЕКТИВНОСТИ ОСУЩЕСТВЛЕНИЯ ГОСУДАРСТВЕННЫХ И МУНИЦИПАЛЬНЫХ ЗАКУПОК В РЕСПУБЛИКЕ КОМИ

The purpose of the article is to create and maintain theoretical and methodological materials for calculating the effectiveness assessment of state and municipal procurement as a single methodology that will meet all the key principles of the contract system and will be focused on the creation and movement in the main directions of its development at the regional level. As a result, the authors carried out a comprehensive assessment of the effectiveness of the state and municipal procurement system at the stage of modern development of the Komi Republic. The authors implemented the total annual volume of purchases, analyzing the main indicators of the procurement of goods, works, services to meet state and municipal needs, considering the structure of competitive procedures and determination of savings based on the results of purchases. The author developed the ways to solve problems that can increase efficiency in state and municipal procurement. Compliance with the recommendations leads to more economical spending of budget funds in the Komi Republic in the implementation of procurement procedures.

Consumer behaviour analysis in video streaming purchases in Indonesia by implementing 7P's marketing strategy using quality function deployment

Video is a technology for capturing, recording, processing, transmitting and rearranging moving images. Videos can be packed on VCDs, DVDs, and Blue-ray discs. In the millennial era, there are many websites and video streaming applications. With smartphones, video streaming applications can be enjoyed anytime and anywhere with a variety of video genres. In addition, video streaming also sell videos legally such as http://www.iflix.com, http://www.hooq.tv, http://www.netflix.com. Video streaming can increase competition to attract conventional video products. In this case, the company needs the right strategy to increase the purchase volume by understanding consumer needs. The objective of the study is to see and analyse consumer behaviour regarding video streaming purchases to improve video streaming recognition in Indonesia. The decision to purchase by consumers is affected by 7P (product, marketing strategies price, place, promotion, people, physical evidence, and process). A 7P marketing strategies is one of ways that can be used to analyse behaviour consumptive in the buying video streaming. In this study, to get the information about the consumption of video done through the questionnaire, data obtained from respondents will be processed using the quality function deployment (QFD) method.

THE UKRAINE ELECTRICITY MARKET: MANAGEMENT AND DEVELOPMENT TRENDS

The new electricity market of Ukraine started working in 2019. It provided a new model for interaction between suppliers and consumers of electricity. At present, electricity is sold under bilateral agreements between producers and suppliers or consumers. The supply is segregated into a separate business, which meets European standards and creates conditions for fair competition. The purpose of the article is to investigate the features of the modern state of management and development of Ukraine’s electricity market and to substantiate proposals for their improvement. The article discusses the main issues concerning the management and development trends of the Ukrainian market for electric power. The entities of the electricity market and features of the functioning of the new energy market of Ukraine are identified. Also, considered are systems of relations between market participants in the realization of purchase and sale of electric energy and/or auxiliary services, transmission and distribution, as well as delivery of electric energy to consumers. Indeed, the introduction of a new electricity market model creates more opportunities for the development of all participants without exception. On the basis of the results of the study, the main accents of the electricity market of Ukraine are selected, which are considered as the main indicators of trade of electric power on a half-yearly basis, as well as prices of products on the «day-ahead» market and internal market. The given system of main indicators and structure of sales and purchase volumes on the electricity market of Ukraine can be a benchmark for improving the efficiency of Ukraine’s electricity market for the next period. The advantages of the new model of the energy market of Ukraine are the destruction of the monopolies of regional energy supply companies. Regional energy supply companies did not always control the quality of energy supply. The independent supplier has leverage and may impose fines for breaches of supply conditions. Ukraine will continue to move along the European vector of energy market development. Poland can be considered as an example of Ukraine’s energy market development. As a result of the development of the energy market in Poland, the former state-owned monopoly companies have lost most of their consumers.