Purchase Quantity Research Articles

Materials inventory optimization using various forecasting techniques and purchasing quantity in packaging industry

Purpose: This paper studies the problem that occurs on material purchase quantity in price uncertainty situation. Larger buying quantity when the price at high will increase the purchase amount while smaller buying quantity could risk the inventory level. The decision on the purchase quantity of a cycle takes future price as input from price prediction output.Design/methodology/approach: This paper examines five price prediction models, Classification and Regression Tree (CART), Random Forest Regressor (RFR), Support Vector Regressor (SVR), Seasonal Autoregressive Integrated Moving Average (SARIMA) and Long Short Term Memory (LSTM) to predict four Petrochemical products, Linear Low Density Polyethylene (LLDPE), Low Density Polyethylene (LDPE), Biaxially Oriented Polypropylene (BOPP) and Cast Polypropylene (CPP) using dataset built from weekly datapoints from January 2020 to June 2023. The most performing model is validated with data from July 2023 to September 2023 where the prediction result is fed into Linear Programming Simplex method to minimize the amount of purchase by making advanced or postpone orders.Findings: Result that RFR performs higher at most products tested, while SVR performs higher in LDPE product. The fitting of RFR and SVR models prediction, as predicted price to Linear Programming that decides optimum purchase quantity, delivers a total 2.2% of purchase amount reduction compared to original purchase quantity reflecting base scenario issued by the planner.Research limitations/implications: This study does not include additional prediction factors such as freight cost and the hyperparameters tuning studies on the existing factors.Originality/value: The novelty of this paper is prediction value is followed up by an optimization model that would guide the Procurement team decisions for future anticipation because imported raw materials should be purchased ahead of time. This research will provide a scientific approach input that would counterbalance or strengthen decision making that is typically made by individuals owning years of experience. This combined approach is rarely researched and has not been done to polymer products.

Analisis Pengendalian Persediaan Bahan Baku Kacang Koro pada Produk Abon Menggunakan Metode Economic Order Quantity dan Desain Kemasan di UMKM Surya Abon

This research aims to produce compatibility between the policies of Abon Surya with the Economic Order Quantity raw material control method, namely the purchase quantity of the Abon Surya policy has an average purchase of 770 kg, for the frequency of purchasing raw materials for jack beans 5 times, for security and point supplies. There is no reordering policy with a total inventory cost of IDR 251,640. Meanwhile, the EOQ method has an average purchase of 1,313 kg. the purchase frequency is only 3 purchases, the security inventory is 90 Kg and the number of reorders is 204 Kg with a total cost of inventory required of IDR 173,254. The cost difference between Abon Surya and the EOQ method is IDR 78,386,417. This shows that there is a saving or reduction in the total cost of inventory needed if Abon Surya can implement the EOQ raw material control method. Apart from that, the packaging used at UMKM Surya Abon for shredded products still uses transparent plastic with stickers, which is less attractive to buyers. Therefore, a new design is needed to attract more buyers.

Replenishment Pricing of Vegetable Commodities in a Supermarket as an Example in China

In this paper, for the automatic pricing and replenishment decision-making problem of vegetable commodities, it is found that there are certain seasonal characteristics in the sales of vegetables in each category, and wavelet analysis is carried out on the daily sales data of single products to get the sales cycle of each category. For the vegetable single product with large amount of data, all single products are divided into four categories of common household vegetables, packaged vegetables, seasonal special vegetables and special vegetables by systematic cluster analysis, and the time distribution characteristics of single products are described by the sales time series of typical members in each cluster. Based on the market demand theory, the cost-plus pricing and sales volume data of the categories were fitted, and the relationship was obtained to be negatively correlated. Taking the purchase quantity and pricing of each category as the decision variables, maximizing revenue as the objective function, and taking the historical maximum purchase quantity of each category and the historical maximum purchase quantity of the superstore as the constraints, a nonlinear programming model was established to formulate the pricing and replenishment strategies for vegetable products. By solving the model, the optimal strategy of replenishment volume and pricing for the future seven-day category is derived, corresponding to the maximum profit of ￥3124.75.

Consumption of Material Goods and Services: Regional Characteristics and Trends

Consumption of material goods and services is a sphere of economic relations that is aimed at satisfying the material, spiritual and intellectual needs of people. Consumption is the most important stage of the reproduction process. characterizes the level and quality of life of the population, reflects the effectiveness of the state’s socio-economic policy. In recent years, against the backdrop of changing socio-economic conditions, the study of patterns, features and trends in the consumption of material goods and services is a fairly relevant and sought-after area of research. This article analyzes the level and dynamics of consumption of goods and services by residents of the Vologda region, examines the features of the structure of consumer expenditures of households in the region, and identifies income and territorial differentiation in the consumer market. The information and empirical basis of the study are the results of monitoring of the Vologda Scientific Center of the Russian Academy of Sciences, carried out in the Vologda region. The results of the study showed that, against the backdrop of an increase in the quantity (volume) of purchases of goods and services, a low level of material consumption opportunities for residents of the region remains, which is due to a fall in real incomes, rising inflation, and negative structural changes in family budget expenditures. Risk categories include representatives of the 20% least affluent group, as well as residents of rural areas, whose consumption level is noticeably lower than the regional average. Improving the situation in the area of consumption of material goods and services by residents of the region will depend on the degree of effectiveness of the measures taken by the federal and regional authorities to bring the economy onto a sustainable development trajectory, increase the income of the population, and overcome excessive income differentiation and property stratification of the population.

Assessment of Awareness, Knowledge, and Perception on the Purchase Intention towards Packaged Milk

India has the highest livestock population in the world with 50 percent of the buffaloes and 20 percent of the world’s cattle population, most of which are milk cows and milk buffaloes. The research was focused on the packaged milk purchasing behaviour of consumer. The study area is confined to Erode district because of its high population and narrowed down to Erode town since the packaged milk purchasing is higher in town area. From each selected wards, 20 sample respondents are randomly selected. A pre-tested questionnaire will be used to collect data for the study. The general characteristics of the sample respondents would help in understanding the nature and behavior of the sample respondents. The general characteristics of sample respondents such as, education, purchase decision of sample respondents etc have a significant bearing on the study. Percentage analysis was used to study the general characteristics of the consumers which included age, education, gender, income, occupation, awareness, preference, knowledge of the respondents, frequency of purchase, type of decision makers, quantity of purchase, place of purchase. Majority of the respondents were aware of branded and non-branded milk. Only few respondents were not aware so suitable step should take to create awareness, so that more customers will get motivated to buy branded and non-branded milk. Knowledge of the respondents on branded milk was depends on consumer interest and also education one of the reason to gain knowledge. Most of the respondents were preferred Aavin because booth there and availability of the Aavin milk is high compared to other brand. So expect Aavin other firms have to follow suitable marketing strategies to increase preference among the consumers. Knowledge of the respondents on branded milk was depends on consumer interest and also education is one of the reason to gain knowledge. About 33 per cent were had energy level knowledge on branded milk. Whereas 67 per cent of the respondents were had energy level knowledge on branded milk. About 11 per cent were had energy level knowledge on non-branded milk. And majority of the respondents 89 per cent were had energy level knowledge on non-branded milk.

Fruitful changes? Exploring household fruit purchase decisions following comprehensive food policy regulations in Chile

Changes in unprocessed healthy food purchases associated with the implementation of comprehensive food policy remain understudied. This study analyzes whether, following the announcement, modification, and implementation of Chile's Food Labeling and Advertising law targeting highly processed food (occurring in 2012, 2015, and 2016, respectively), households improved their fruit purchase decisions: purchase participation (i.e., buying likelihood) and purchase quantity. Expenditure data from a representative sample of Chilean households were employed, covering two consecutive survey waves conducted in 2011/2012 and 2016/2017. After controlling for socioeconomic factors (e.g., prices and income), results indicate that only purchase participation increased, providing weak support for positive spillover effects of a comprehensive food policy on fruit purchases. Subsample analyses reveal that this increase was driven by college-educated, childless, and low-income households and was stronger for sweeter and more convenient fruits. Considering that households in Chile do not meet health recommendations for daily fruit intake, additional policy efforts targeting healthy, unprocessed food consumption could be considered.

A purchaser's optimal procurement strategy under emergencies

This paper investigates a purchaser's optimal procurement strategy under emergencies. The occurrence of emergencies often leads to sharp fluctuations in prices and weakens supply stability, which increases procurement risks for purchasers. In this study, we use the option contract to actively respond to market fluctuations and reduce procurement risks caused by emergencies. If there is insufficient inventory due to occurrence of emergencies, part or all of the shortages can be met by an emergency replenishment. Then, we conduct an in-depth research on the optimal option procurement strategy for purchasers under emergencies. The results show that, a higher emergency replenishment rate leads to a smaller option purchase quantity if the shortage cost is not considered, since the emergency replenishment can save part or all of the shortages. If the shortage cost is considered, both over-purchasing and under-purchasing of options lead to corresponding losses, and then the trend in a purchaser's optimal option purchasing decision is decided by the dominance of the two types of losses. Finally, we summarize the results of the study to give managerial insights into the optimal option purchasing strategies for purchasers under emergencies.

Farmers’ Adoption of Finger Millet Production Technologies and the Impact on Finger Millet Yields

Low remuneration and poor adoption of Finger millet [Eleusine coracana] production technologies were major constraints in yield gap in finger millet. Therefore, evaluation of production potential, adoption, economic and other benefits of the technologies in social perspectives of the farmers was undertaken. The study was conducted in two districts of Karnataka, India where the frontline demonstrations programme organized during the five years from 2017-18 to 2021-22 in 200 farmers’ fields. The knowledge, adoption and impact were measured by following before and after method, and data was collected through survey, focussed group discussion and personal interview methods. The demonstrated technologies resulted into increase in Knowledge over pre demo in use of high yielding variety (85%) followed by use of nitrogen (Urea) (62%), seed treatment (62%), use of FYM (56 %). Increase in adoption over pre demo was found in use of high yielding variety 82 % followed by use of nitrogen (62%), seed treatment (55%), use of FYM (48%). The higher adoption of the demonstrated technologies (71%) by the farmers in Karnataka led to higher grains production (33%) with better quality (65%) and fodder yield by 38% over pre-FLD stage. The increased yields not only enabled them to obtain higher net returns (55%) and incremental increase of benefit-cost ratio (25%) but also motivated to increase in area under finger millet (20%) significantly than the pre-FLD stage. Whereas, very low increase in cost of production (10%) over the pre-FLD stage was observed. Age, education, family size, annual income, institutional support, extension contact, herd size, and utility of grain and fodder were found to be significant in explaining the variation in their adoption level of demonstrated finger millet production technologies. Among the constraints, availability of labour, wild animals (deer and wild boar) and availability of seed are the major production constraints and price fluctuation, limited quantity purchases by government, delay in payment by government, and high commission from APMC are the major market constraints. To boost-up the adoption, large family size of the farmers, their dependency on farming and continuing newly selected farmers with field demonstration of location-specific low-cost technologies up to five years should be considered.

Public food procurement and food security: an assessment of the impacts of the PAA on family farming in Brazil

Public Food Procurement (PFP) can be used as an important social intervention tool to promote food security for specific groups, foster rural development, and drive local and regional food economies towards more sustainable paths. The Food Acquisition Program (PAA) is a Brazilian government program created to encourage family farming and combat food insecurity and nutritional risks among socially vulnerable people. This study aimed to estimate the impact on gross agricultural income and production diversity for family farmers who delivered products for the main modality of this program: Simultaneous Purchase and Donation (CDS). We utilized an empirical difference-in-differences strategy, using microdata from government administrative records that cover all PAA-CDS purchase amounts in the country, as well as information on about two million family farming production units for the period between 2009 and 2017. Our findings indicate that PAA-CDS contributed to an average increase of 24.2% in farmers' gross income from production. The poorest benefited the most, with an increase of 45.9% for farmers in the 10th percentile of gross income. Regarding the diversity of production, we estimated a significant positive impact of the program on the diversity index and the number of products, as well as a reduction in the specialization of gross income. These results suggest that the program's design can be effective for its primary purposes.

Assessment on the User Interface of a Select Consumer Mobile Application and its Effect to Purchasing Behaviour of Generation Z

The research assessed the User Interface of a Select Consumer Mobile Application and its effect to the buying behaviour of Generation Z. The Visual Appeal, Navigational Content and Application’s Data Modelling are used as factors for the Mobile App User Interface while Frequency, Quantity and Timing of Purchase are used for Purchase Behaviour. The research is quantitative in nature and utilized 250 respondents selected by way of purposive and random sampling. Results revealed that, in terms of the User’s Interface, respondents expressed a Strong Agreement on the aspect of usability in terms of features and functionalities of the select Consumer Mobile Application. Similarly, a Strong Agreement is also expressed by the respondents towards influence of the user interface in their Purchasing Behaviour. Also, result revealed that the User’s Interface of the Select Mobile Application Strongly Influenced the Purchasing Behaviour of the respondents.

Investment Decision Using Technical Analysis: A Study on Selected Stocks in Indian Stock Market

Technical analysis is a methodology in financial markets that asserts its capability to predict future stock directions by scrutinizing historical market data, patterns in price movements, and correlations between price and volume. Traders widely utilize these data in their decision- making processes. The approach also takes into account the real-time behavior of market prices and volumes, operating under the assumption that these are the most influential factors in determining a stock’s or market’s future trajectory. Investors often grapple with decisions regarding which stocks to buy, the optimal purchase quantities, and when to execute selling or holding actions to maximize profits in the trading period. This research delves into these considerations, offering insights for short-term traders by analyzing the stock price trends of twelve companies across three distinct sectors over the 2020-2022 period.

SIKAP, KEPUASAN DAN LOYALITAS KONSUMEN SUSU SEGAR YU-ONE MILK DI KOTA BANDAR LAMPUNG

This research aims to determine the attitudes, purchasing patterns, satisfaction, and loyalty of fresh milk consumers of Yu-One Milk at Jalan Sultan Agung, Way Halim, Kedaton District of Bandar Lampung City. The research method is a survey. The number of respondents in this research are 60 people, selected by non-probability sampling technique, namely accidental sampling. The research data are analyzed by quantitative descriptively using the Fishbein multi-attribute model, Customer Satisfaction Index (CSI) and the loyalty pyramid. Data collection was carried out in October-November 2022. The results showed that the consumers’ attitude toward multi-attribute of Yu-One Milk fresh milk was in the good category, in which score was 181.72 and the most favored attribute by consumers was friendliness services. Most of Yu-One Milk consumers (25%) bought fresh milk with chocolate flavor variants. The average frequency of purchasing Yu-One Milk fresh milk was twice per month with a purchase expenditure of IDR 51,883.00/month. The average purchases amount of Yu-One Milk fresh milk was 1,377 ml/month with the purpose of purchasing to eliminate hunger/thirst (46.67%). Yu-One Milk fresh milk consumer satisfaction was in the very satisfied category with a CSI value of 83.61. Yu-One Milk consumer loyalty was quite good in the form of an inverted pyramid. The switcher buyer value was 46.67%, the habitual buyer value was 48.83%, the satisfied buyer value was 90.00%, the liking the brand value was 86.67% and the committed buyer value was 83.33%. Keywords: attitude, consumer loyalty, fresh milk, purchase pattern, satisfaction.

How do physical and social servicescapes shape the effects of positive affective displays on customer purchase outcomes?

PurposeThis study aims to use emotions-as-social information theory to investigate how physical (customer perceived store atmosphere) and social servicescapes (customer information searching) influence the effects of employees’ positive affective displays on customer outcomes via customer positive moods and positive expectation disconfirmation.Design/methodology/approachThis research included two studies, each using a distinct research design, to empirically test the proposed model. Study 1 involved 200 observational data points on objective purchase amounts from designer watch shops. In Study 2, data were collected from 230 customers in designer jewelry stores.FindingsThe results of path analyses revealed that: employee positive affective displays are positively associated with customer purchase outcomes; employee positive affective displays had positive indirect effects on customer purchase outcomes by enhancing customer positive moods and positive expectation disconfirmation; these positive indirect effects were strengthened when customers engaged in information search behaviors; and these positive indirect effects were attenuated when customers perceive store atmosphere as favorable, indicating a substitution effect of customer perceived store atmosphere.Originality/valuePrevious research has not thoroughly examined the role of the servicescape in moderating the effects of employees’ positive affective displays on customer purchase outcomes. This present study not only clarified the affective and cognitive mechanisms that link employees’ positive affective displays on purchase outcomes but also identified servicescape as a critical boundary condition of these effects.

The influence of anchor burnout mood on consumers’ consumption psychology and behavior

This study investigated the effects of anchor burnout on consumer consumption psychology and behavior. Through the questionnaire survey, we found that anchor burnout had a significant impact on consumers’ purchase intention, purchase amount, satisfaction and loyalty. The experimental results show that the more serious the anchor burnout mood, the lower the purchase intention and purchase quantity of consumers and the lower the satisfaction and loyalty. These findings contribute to understanding the impact of anchor emotions on consumer behavior and provide useful reference for relevant businesses and researchers. The results of this study have certain guiding significance for understanding the influence of anchor emotions on consumer behavior and formulating corresponding marketing strategies.

Nudging plant-based alternatives to meat and dairy in a real-life online supermarket: A randomized controlled trial

A shift from predominantly animal-based to plant-based consumption can benefit both planetary and public health. Nudging may help to promote such a shift. This study investigated nudge effects on plant-based alternatives to meat and dairy in an online supermarket. We conducted a two-arm, parallel-group, randomized controlled real-life online supermarket trial. Each customer transaction was randomized to a control arm (regular online supermarket) or an intervention arm (addition of placement, hedonic property and dynamic social norm nudges promoting meat and dairy alternatives). Outcomes were the aggregate of meat and dairy alternative purchases (primary outcome), the number of meat purchases, dairy purchases, meat alternative purchases, and dairy alternative purchases (secondary), and retailer revenue (tertiary). Generalized linear mixed models with a Conway–Maxwell Poisson distribution were used to estimate incidence rate ratios (IRRs). Analyzed data included 8488 transactions by participants (n = 4,266 control arm, n = 4,222 intervention arm), out of which 2,411 (66%) were aged above 45 years, 5,660 (67%) were females, and 1,970 (23%) lived in socially disadvantaged neighborhoods. Intervention arm participants purchased 10% (IRR 1.10 (95% CI 0.99–1.23)) more meat and dairy alternatives and 16% (1.16 (0.99–1.36)) more meat alternatives than control arm participants, although these findings are not statistically significant. There was no difference in dairy alternative purchases (1.00 (0.90–1.10)). Intervention arm participants purchased 3% less meats (0.97 (0.93–1.02)) and 2% less dairy products (0.98 (0.95–1.02)) than control participants. Retailer revenue was not affected (0.98 (0.95–1.01)). Online nudging strategies alone did not lead to a statistically significant higher amount of plant-based purchases, but replication of this work is needed with increased study power. Future studies should also consider nudging strategies as part of a broader set of policies to promote plant-based purchases. Trial registrationProspectively registered on 14th of May 2022. ISRCTN16569242 (https://doi.org/10.1186/ISRCTN16569242).

Central bank asset purchases and lending: Impact on search frictions

We investigate the impact of two central bank policies, asset purchases and asset lending, on the search frictions in the government bond market in Japan. We build a search-theoretic model to explore the impact of a central bank’s securities lending facility (SLF) by introducing a central bank as a lender. We test model predictions using intraday data from an electronic platform for Japanese government bonds. First, we find large-scale asset purchases (LSAPs) increase order imbalance in the repurchase agreement (repo) market. Threshold analysis reveals that asset purchase amounts exceeding 0.18% of the outstanding, which corresponds to 38.98% of our sample, cause a significantly higher imbalance. Second, the SLF has a floor effect on the repo rate by affecting dealers’ choices between the repo market and the SLF. Third, the novel friction measures we test show that LSAPs and the SLF have opposite influences on bargaining power in the repo market.

Analisis Pengendalian Persediaan Barang Fast Moving Dan Efisiensinya Dengan Menggunakan Metode Economic Order Quantity (EOQ): Studi Kasus Pada CV. X

<p><em>In retail companies, inventory is an important component for the operation of the company. The purpose of this research is done to find out the inventory control system carried out by the company, inventory control analysis CV. X with the EOQ method, knowing the economical inventory cost and optimum purchase frequency with the EOQ method, and knowing the amount of safety stock and when will be reordered (reorder point) inventory items on CV. X. The type of research used is quantitative research with a descriptive approach. This analysis is carried out by comparing inventory control policies implemented by companies and inventory control using the EOQ method. The results of this research show that inventory control with the EOQ method can save total inventory costs of Rp 45,333,016 or 56% more efficient when compared to total inventory costs using company policies. In addition, the use of the EOQ method can produce optimal quantity and frequency of purchases as well as the application of safety stock and reorder points.</em></p><p><em> </em></p>

Electronics Spare Part Goods Demand Forecasting Using Markov Model

Customer demand forecasting plays an essential part in inventory management in retail companies. Accurate customer demand forecasting will increase a company's competitiveness and play a crucial role in making the right decisions for inventory management. Without demand estimation, products are often purchased more than needed, resulting in overstock or understock product storage in the warehouse. In this paper, we present the results of the Markov Chain method for predicting the quantity of demand for goods in the future to assist decision-making regarding the procurement of commodity goods within the company, especially in the procurement of electronics spare parts in retail companies. This study aims to develop a software-based forecasting system for retail companies using the Markov Model with predictive capabilities. The system will also provide purchasing quantity recommendations to fulfill the stock, calculated from the minimum stock and forecasted demand from customers and suppliers. Using the Markov Chain model, this study predicts electronics spare parts demand using data on item sales during 2022 in a retail company. The forecasting of electronics spare part demand resulted in 88.2% accuracy. The software-based forecasting system has been implemented and tested using black box testing. The testing result shows that the Markov forecasting system is feasible and can be used as a reference in providing electronics spare parts purchasing recommendations for retail companies.

Automatic Pricing and Replenishment Decisions of Vegetable Products Based on Machine Learning

The objective of this paper is to address the replenishment challenge caused by the limited shelf life of vegetables and maximize the profit potential of a diverse range of vegetables, based on extensive data analysis encompassing vegetable sales rates and gross profits. In this study, machine learning techniques, including the Spielman correlation coefficient, are employed to derive the demand price regression curve and R^2 value. Subsequently, a random forest regression model is utilized for training and predicting data, while an ARIMA model based on time series data is applied for individual data processing. The expected return under current prices is calculated iteratively until convergence is achieved in terms of optimal expected returns, best prices, and ideal replenishment strategies. The stability of the data is assessed using the ADF test with satisfactory results obtained. This research yields numerous computational outcomes through machine learning methodologies. Among these findings, broccoli emerges as the most profitable vegetable with the highest purchase quantity and sales volume; meanwhile, Yunnan lettuce stands out as having the largest catch quantity. Demand exhibits a predominantly negative correlation with price; furthermore, after incorporating constraints such as "minimum packaging amount," medium-priced dishes yield maximum profitability. These findings hold significant value and practical implications for real-life problem-solving.

Replenishment And Automatic Pricing Strategy for Vegetable Products Based on Genetic Algorithm

In order to improve the accuracy of replenishment and pricing of vegetable commodities sold in supermarkets, and to maximise the benefits of vegetable commodities sold in supermarkets, this paper comprehensively establishes a strategic planning model for replenishment and automatic pricing of supermarkets. Firstly, we carry out descriptive statistical analysis and non-linear fitting on the historical sales data of supermarkets to find the distribution pattern of the sales of each single product of vegetables, and then find out the relationship between each single product of vegetables through correlation analysis. and then find out the relationship between each vegetable item through correlation analysis. After that, we built an LSTM time series forecasting model based on the cost data to predict the replenishment volume of the six vegetable categories in the coming week. Finally, in order to maximise the revenue of the superstore, we constructed a pricing planning model for the combination of vegetable categories, and solved the optimal purchase quantity and pricing strategy based on genetic algorithm.