Sales Volume Data Research Articles

Menu Engineering Analysis: An Industrial Reference For Tourism Students

This research paper examines the classification of the menu items at Essier restaurant, located within The Vasini Boutique Hotel in Bali, Indonesia, using the Menu Engineering Analysis methodology. Through the use of Tables and Matrices, the study presents the findings derived from a qualitative approach of analyzing sales volume and contribution margin data of menu items from January to December of the corresponding year. The study identifies 31 menu items and their classification mapping, which shows that the majority of the items are classified as Dogs (35.48%), followed by Stars (32.26%), Plough Horses (22.58%), and Puzzles (9.68%). This study highlights the significance of periodic menu engineering analysis by the Essier Restaurant Management to improve sales and restaurant profitability. In conclusion, the menu engineering method is an effective tool for ensuring the popularity and profitability of the restaurant's menu offerings.

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.

Sales forecasting and classification model and pricing research of agricultural perishables based on STL-ARIMA

The prediction of sales volume for agricultural perishable goods is crucial for small-scale merchants to formulate corresponding procurement strategies. Accurate sales volume forecasting helps merchants reduce the risk of excess inventory, establish prudent and appropriate procurement strategies, and provide suggestions for product pricing. To further accurately explore the sales volume patterns of various perishable goods, this study classifies existing data into individual products using the STL (Seasonal-Trend decomposition using Loess) algorithm, revealing the characteristics of each product's sales volume over time. Based on the existing sales volume data, the ARIMA model is used to predict the sales volume of specific categories of goods. A multivariate linear regression model related to pricing, based on existing cost and pricing data, is established to provide merchants with pricing suggestions.

Vegetable Stocking and Pricing Model Based on Time Series Forecasting and Non-linear Programming

This study aims to help fresh produce superstores develop vegetable replenishment and pricing strategies to maximize their benefits. By analyzing historical sales records and customer demand, the study used an ARIMA model to predict future demand and a planning model to optimize superstore revenues. The study also analyzed the sales data of 6 major categories and 246 individual types of vegetables and found that flower and leafy vegetables were the most popular in the market. By performing Spearman correlation analysis on the sales volume data, the study obtained the two pairs of vegetable categories with the highest degree of correlation. In addition, a positive correlation between sales volume and total price was fitted by linear regression and converted to a negative correlation between cost-plus pricing and sales volume. Finally, past costs, damage rates, price factors, and demand were taken into account to optimize each day's data individually to maximize the superstore's revenue, where the maximum profit on the first day was $1,520.6.

Vegetable Price and Supply Forecast based on the Taboo Search Slgorithm

Vegetables, as an indispensable consumer goods in the daily life of consumers, their price and supply have a great impact on the sellers, urban and rural residents and the whole country. In this paper, the sales flow and loss of 251 vegetables in a supermarket within three years are selected as the test data. On the basis of the analysis of the historical sales volume, price and loss data of vegetables, the vegetable price and supply prediction model based on the taboo search algorithm is put forward from the perspective of sellers. First of all, according to the recent sales data, the average daily average sales volume of various single products is obtained, and the varieties that meet the display demand are determined as available varieties, and 36 available varieties are obtained. Further use of 0-1 planning to determine 27-33 available varieties. The linear regression was used to analyze the relationship between the price of each item and obtain the linear regression equation. Significance analysis of the equations showed a high degree of fit. Finally, with the benefit as the objective function, the optimization model is established combined with the above constraints and solved using the taboo search method. The results of the model solution show that under the constraints, the maximum revenue of July 1 is 1787.61 yuan, and the replenishment quantity and pricing of 28 single products sold at this time can be obtained. Finally, the reliability of the model was further tested by using the time-series prediction. This paper can not only effectively predict the price and sales volume of vegetables, but also formulate reasonable vegetable replenishment and pricing strategies for the sellers, but also has important guiding significance for the sales of other commodities.

Research on Vegetable Product Pricing and Replenishment Decision Based on Linear Regression and ARIMA Model

With the rise of fresh food supermarkets, how to automatically price and restock vegetable products has become a major challenge for many businesses. To develop a restocking and pricing plan for vegetable products in supermarkets, we first calculate the cost profit margin, standardize the profit margin and total sales volume data, and then incorporate vegetable categories into a linear regression model using dummy variables, We found a significant negative correlation between profit margin and total sales volume, and obtained the product pricing strategy using the linear equation of profit margin. After conducting ADF testing, the number of autoregressive terms and the average number of sliding terms of the Time Series (ARIMA) model were determined based on the test set results, and the model was used to predict the total daily replenishment of each vegetable category in the next week. This study has reference value for vegetable restocking and pricing decisions.

Regulatory enforcement of the marketing of fixed-dose combinations in India: a case study of systemic antibiotics

BackgroundIn India, states have licensed the manufacture of large numbers of fixed-dose combination (FDC) drugs without the required prior approval of the central regulator. This paper describes two major regulatory initiatives to address the problem, which began in 2007 and 2013, and examines whether they have been sufficient to remove centrally unapproved systemic antibiotic FDCs from the market.MethodsInformation was extracted from documents published by the central regulator and the ministry of health, including the National List of Essential Medicines (NLEM), and court judgments, and analysed alongside sales volume data for 2008–2020 using PharmaTrac market dataset.ResultsThe regulatory initiatives permitted 68 formulations to be given de facto approvals (‘No Objection Certificates’) outside the statutory regime, banned 46 FDCs and restricted one FDC. Market data show that FDCs as a proportion of total antibiotic sales increased from 32.9 in 2008 to 37.3% in 2020. The total number of antibiotic FDC formulations on the market fell from 574 (2008) to 395 (2020). Formulations with a record of prior central approval increased from 86 (2008) to 94 (2020) and their share of the antibiotic FDC sales increased from 32.0 to 55.3%. In 2020, an additional 23 formulations had been permitted de facto approval, accounting for 10.6% of the antibiotic FDC sales. Even in 2020, most marketed formulations (70.4%, 278/395) were unapproved or banned, and comprised a 15.9% share of the antibiotic FDC sales. The share of NLEM-listed antibiotic FDC sales increased from 21.2 (2008) to 26.7% (2020).ConclusionThe initiatives had limited impact. Regulatory enforcement has been slow and weak, with many unapproved, and even banned, FDCs remaining on the market.

Systemic anti-cancer therapy patterns in advanced non-small cell lung cancer in Europe

BackgroundSystemic anti-cancer therapy (SACT) is the recommended treatment modality in patients with advanced non-small cell lung cancer (aNSCLC) in clinical guidelines. SACT options in aNSCLC have multiplied in recent years with the introduction of immunotherapy and targeted therapy. This article presents findings from the first comparative analysis of SACT patterns in Europe. MethodsSACT rates in aNSCLC were estimated as the ratio between the number of patients treated with SACT (chemotherapy, immunotherapy, targeted therapy) and the number of potentially eligible patients for SACT in 11 countries (Belgium, Bulgaria, Finland, Hungary, Ireland, Netherlands, Norway, Poland, Portugal, Romania, UK) between 2014 and 2020. Treated patients were estimated by combining national sales volume data of cancer drugs and average drug use per patient based on clinical trials. Potentially eligible patients were estimated from national epidemiological data. ResultsSACT rates in aNSCLC differed greatly, ranging from around 30 % in Hungary, Poland, and the UK to almost 60 % in Ireland, Norway, and Portugal in 2014. SACT rates seemed to increase over time in most countries, but differences were still large by 2020, ranging from around 40 % in the UK to 75 % or more in Belgium, Norway, and Portugal. Even in countries with the highest SACT rates, far from all patients seemed to receive guideline-recommended SACT options, as underuse of immunotherapy and targeted therapy was common. ConclusionUp to 35 % of eligible patients with aNSCLC receives no SACT in certain European countries, although improvements have been achieved over time. The use of immunotherapy and targeted therapy is suboptimal even in countries with high SACT rates, indicating room to improve the quality of care and patient outcomes. Policy summaryMeasuring if and what kind of therapy cancer patients have access to is vital to assess quality of care. The care of aNSCLC patients seems to be suboptimal in Europe, due to factors such as exclusion of patients with moderate performance status from SACT, limited resources for diagnostic testing, long reimbursement timelines and slow adoption of new medicines in clinical practice.

A REVIEW OF THE ECONOMIC IMPACT OF THE COVID-19 PANDEMIC ON THE AUTOMOBILE INDUSTRY IN MALAYSIA

The COVID-19 pandemic has resulted in a disastrous impact on the production and sales of many industrial sectors. Voluminous past literature has shed light on the negative implications of the pandemic crisis on these sectors. However, this paper aims to draw light on the impact of the pandemic crisis on the automotive industry, one of the nation’s largest industries. A comprehensive review will be performed to demonstrate the significant implications of the COVID-19 pandemic on the automobile industry. In addition, an evaluation of the government’s measures to mitigate the negative impacts of COVID-19 on individuals and economic sectors is presented in this paper. An examination of the effectiveness of the government’s move in assisting the recovery of the industrial sector, specifically the automotive sector, is done through the evaluation of the sales volume data. Therefore, the implications of this study are to demonstrate the association between the effect of the pandemic crisis and the automotive sector’s production. Secondly, to provide a review of the government’s measures and to present its association with the sales volume in gauging the effectiveness of the measures adopted. The findings of this study presented robust evidence of the negative implications of the COVID-19 pandemic on automobile production and sales volume. Notably, the decline of sales and production units is more apparent during the period of the nation’s lockdown due to COVID-19. Besides, this study has made a noteworthy contribution by discussing the government’s policy measures implemented during this pandemic crisis.

Probability distribution and recommended values of passenger car external dimensions in mechanical parking garage design

ABSTRACT In order to determine the external dimensions of passenger car, to meet the current parking needs when designing a mechanical parking garage. In this study, 7193 groups of external dimensions and sales volume data of passenger car in the Chinese market from 2009 to 2020 are collected. Then, appropriate probability distributions are used to fit the collected data. Combined with their actual market share, the recommended external dimensions of sedan, SUV and MPV, separately, as well as all of them together, defined as general vehicles, are given by using probability statistics method. It is concluded that the external dimensions of sedan and SUV obey the t Location-Scale distribution, while MPV follows the mixed normal distribution. The length and width of general vehicles follow the t Location-Scale distribution and the height obeys the mixed normal distribution. The length, width and height of sedan are 5100 mm, 1890 mm and 1560 mm, respectively. The ones of SUV are 4950 mm, 1940 mm and 1850 mm, respectively, and for MPV they are 5300 mm, 1900 mm and 2000 mm, respectively. The corresponding dimensions of the general vehicles are 5150 mm, 1930 mm and 1900 mm, respectively. The proposed passenger car external dimensions can provide guidance for the garage design, aiming at the optimum space exploitation.

Boston Consulting Group (BCG'S) Analysis On Powder Coffee 1001 Bengkulu City

In implementing the marketing strategy, it is always related to marketing recommendations consisting of four variables, namely: product, price, place, promotion. BCG analysis is based on the basic premise that a company should have a balanced portfolio of business, which produces more than the amount it uses. Its role is determined by two factors, namely: (1) Market Growth Rate (2) Relative Market Share. The BCG analysis has 4 cells representing 4 combinations showing the lowest growth rate and market share, namely: stars, cash cows, dogs, and question marks. The data collection methods used in this writing were the observation method, the interview method (unstructured), and the documentation method. BCG analysis was carried out based on data on the sales volume of Usaha Kopi Bubuk 1001 of Bengkulu City in 2018 and 2019 which were compared with the sales volume data of Usaha Kopi Bubuk Aroma in 2019, to obtain a relatively high level. From the results of research with BCG analysis, it can be seen that the market growth rate of Usaha Kopi Bubuk 1001 of Bengkulu City in 2019 is 14% and the relative market share is 1.6x, then Usaha Kopi Bubuk 1001 of Bengkulu City is in the Star position, which indicates that growth high market and relatively high market share, and it is related to the Product Life Cycle, the product position of Usaha Kopi Bubuk 1001 of Bengkulu City is in the Growth stage, so the strategy used by Usaha Kopi Bubuk 1001 of Bengkulu City is the Hold strategy.

Use of budget savings from patent expiration of cancer drugs to improve affordability and accessibility

BackgroundThe introduction of generics after the loss of patent exclusivity plays a major role in budget savings by significantly decreasing drug prices. The aims of this study were to estimate the budget savings from off-patent cancer drugs in 2020–2024 and to inform decision makers on how these savings could be used to improve the affordability of innovative cancer treatments in South Korea.MethodsA model was developed to calculate budget savings from off-patent cancer drug use in Korea over 5 years (2020–2024). Cancer drugs with one or more valid patents that expire between 2020 and 2024 in Korea were selected. Key input parameters in the model included market share of generics, market growth, and prices of originators and generics. To reflect market dynamics after patent expiration, the trends of the off-patent market were estimated using historical sales volume data of IQVIA from 2012 to 2018. The study assumed that the prices of off-patent drugs decreased according to the price regulations set by the Korean government and that the off-patent market sales volume did not grow. Sensitivity analyses were performed to investigate the uncertainty in model input parameters.ResultsA total of 24 cancer drugs which met selection criteria were identified. In the base case analysis, patent expiration of cancer drugs between 2020 and 2024 could lead to a spending reduction of ₩234,429 million ($203 million), which was 20% of the cancer drug expenditure in the 5-year period. The savings ranged from ₩157,633 million ($136 million) to ₩434,523 million ($376 million) depending on the scenarios in sensitivity analyses.ConclusionsThe findings indicate that patent loss of cancer drugs could lead to a 20% reduction in spending on cancer drugs over the next 5 years in South Korea. The savings could be used to improve the affordability of innovative, advanced cancer drugs for 94,000 cancer patients by reallocating the budget savings from patent expiration.

Process and Method for Implementation of Automated Nutrient Profiling Reporting for a Global Food and Beverage Portfolio

Abstract Objectives With the increasing need for dynamic and flexible nutrient profiling of foods and beverages, PepsiCo has expanded capabilities to report on global nutrition data for business guidance and reporting to regulatory and health agencies. Additional processes were established to integrate nutrition and finance information and influence the long-term data strategy needs of the organization. Methods A multidisciplinary team of nutrition science, finance and IT professionals was assembled to systematically collect and link nutritional and financial data. A controlled, centralized database was created with data from 2015 to present from multiple data sources. Data quality is reviewed quarterly. Dashboards, scorecards and other reporting outputs were created (Tableau software, 2019.02) with end-user input, to measure performance against country-specific regulations, Front-of-Pack (FOP) labeling requirements and internal nutritional guidelines. Results Nutrition data from > 40,000 products are captured annually and linked with sales volume data. There was a 2.5-fold increase in countries contributing data since 2015 (10 vs 26 markets), representing >80% of the company's annual food/beverage sales volumes. Current reports focus on analyzing nutrients-to-encourage (protein, fiber, specific vitamins and/or minerals), food-groups-to-encourage (fruits, vegetables, whole grains, fat-free/low-fat dairy and nuts/seeds/legume) and nutrients-to-limit (saturated fat, sodium, added sugars, trans-fat). Dashboards are currently utilized by 9 company functions, supporting several requests, including national nutrition regulations (n = 2 dashboards), FOP labeling systems (n = 2), retail store requirements (n = 1), internal sustainability goals (n = 3) and customized reports (n = 40). Across all iterations, dashboards have received >1000 views. Conclusions Automated nutrient profiling has been successfully implemented by a multidisciplinary team. Dashboards provide end-users with a timely and efficient tool to dynamically analyze PepsiCo's product portfolio guiding short- and long-term business decisions. Future work includes informing opportunities to improve the nutrient profile of PepsiCo's portfolio and increasing data availability and analysis. Funding Sources PepsiCo Inc.

OPTIMIZATION PLAN FOR EXCESS WAREHOUSE STORAGE IN E-COMMERCE–BASED PLANT SHOPS: A CASE STUDY FOR CHINESE PLANT INDUSTRIAL

The rapid development of e-commerce in China has played a critical role in the development of the national economy and ongoing modernization. The plant industry is unique among industries that employ e-commerce sales models because its products exhibit special characteristics such as high death and damage rates. Therefore, its e-commerce and logistical requirements are stricter than in other industries and, as a result, excess warehouse storage can be extremely difficult for e-commerce–based plant shops to manage. Numerous studies have indicated the need to identify a product’s most up-to-date market conditions, as well as the type, function, and size of warehouses. Therefore, based on a case study, this study proposes an optimization plan for solving excess warehouse storage in e-commerce–based plant shops. First, sales volume data of the case company, Enterprise A, were analyzed to predict future sales. Then, entropy and the technique for order preference by similarity to an ideal solution were used to construct the decision-making model. Finally, a cloud warehouse–based optimization plan was proposed to solve excess warehouse storage in e-commerce–based plant shops. This plan can serve as a reference for decision-makers or executives in e-commerce–based plant shops when handling excess warehouse storage.

Budget Impact of Switching to Biosimilar Trastuzumab (CT-P6) for the Treatment of Breast Cancer and Gastric Cancer in 28 European Countries.

As the economic burden of treating cancer patients has been soaring in European countries, performing a budget impact analysis is becoming one of the requirements for payers' application dossiers. The objective of this study was to estimate the budgetary impact of introducing the biosimilar trastuzumab (CT-P6) from the payer's perspective and to determine the number of additional patients who could be treated with resulting savings in 28 European countries. A budget impact model was developed to analyze the financial impact of switching from originator trastuzumab to biosimilar CT-P6 in the treatment of early and metastatic breast cancer and metastatic gastric cancer with a time horizon of 1-5 years. Budgetary savings and the number of patients potentially affected were measured based on epidemiological and sales volume data. The base-case analysis assumed that the price of CT-P6 is 70% of the originator price, the switching rate of originator to CT-P6 in the first year is 20%, and the annual growth in the switching rate for each subsequent year is 5%. For analyses using the base-case scenario following CT-P6 introduction, the total estimated budgetary savings over a 5-year period (depending on the scenario) ranged from €1.13 billion to €2.27 billion based on epidemiological data, or from €0.91 billion to €1.82 billion based on sales volume data. In the first year only, the projected budgetary savings ranged from €58 million to €136 million, and the number of additional patients who could be treated using the savings ranged from 3503 to 7078 by sensitivity analysis. The conducted budget impact analysis assessing a switch from originator trastuzumab to biosimilar CT-P6 in 28 European countries indicates that budget savings could be between €0.91 billion and €2.27 billion over the next 5 years. These savings could be used to help improve patient access to local biologics in their respective countries while simultaneously strengthening the overall public health landscape across the European Union.

The impact of newly approved drugs on clinical and operational strategies for multiple myeloma clinical trials.

e19511 Background: The global burden of multiple myeloma (MM) has increased steadily in last 3 decades. The IARC reports there were ~160,000 new cases worldwide in 2018. There has been an increase in the development and approval of more effective targeted therapy options (new immunomodulatory agents, proteasome inhibitors, and monoclonal antibodies); this, coupled with high adoption of these therapies presents a major challenge in enrollment of current ongoing clinical trials. We assessed the impact of near-term regulatory approvals on clinical trial enrollment. Methods: Public domain clinical trial enrollment data from MM studies (Phase I, I/II, II) closed/completed between 2011-2018 were used to determine enrollment trends pre and post 2014. We leveraged real-world medical claims data to project/model adoption of recently approved drugs in the U.S.; additionally, drug sales volume data was used to evaluate ex-US national adoption trends. The utilization rates of 5 recently approved drugs by regimen and line of treatment was determined. Results: In the U.S., there is a 13% increase in median enrollment duration with a corresponding 25% decrease in median p/s/m enrollment in MM studies, irrespective of phase, where enrollment was completed between 2015 -2018 compared to 2011-2014. We hypothesize that one of the factors for this increase in enrollment timeline is the approval and adoption of newly approved therapies post 2014. Two of the five recently approved drugs show a steady increase in the number of patients treated over 2016, 2017 and 2018, while one of the drugs plateaus over the same period. Outside of the U.S., our analysis confirms the existence of gaps in time to approval /adoption of recently approved drugs; for example, we observe a two-year delay in approval/adoption for one of the drugs in France compared to the other countries in Western Europe. Conclusions: There are over 10 investigational MM drugs currently in development which are anticipated to be granted approval between 2019-2021. Factoring the real-world adoption of near-term drug approval into global clinical and operational strategies offers insights into mitigating potential future enrollment challenges.

Narrative Gamification as a Method of Increasing Sales Performance: A Field Experimental Study

There is ongoing dispute whether gamification is an effective tool in increasing sales performance. Furthermore, there is a lack of evidence of gamification being a job performance management tool. After the discussion of elements of gamification (with a focus on narration) and the mechanism of this procedure, a field study was conducted to investigate whether implementing narrative gamification within a company will increase sales performance. The study involved 81 employees of two comparable franchise units. Over a period of two months, in one franchisee the employees were working on their regular basis, while narrative gamification took place in the second franchisee. The basic measures were the sales volume data and sales change rates of the two telecommunications products. Tests for difference and effect size were employed. The results of the intervention conducted have shown that narrative gamification had a positive impact on sales performance after two months. Not only did the sales performance in the gamified franchisee increase, but the increase exceeded that of the other franchisee.

Fast Food Restaurants and Convenience Stores: Using Sales Volume to Explain Crime Patterns in Seattle

This study investigates how convenience stores and fast food restaurants influence crime patterns over time. Using sales volume data from fast food restaurants and convenience stores, we examine streetblock crime levels over a seven year period in Seattle using multilevel models. Results demonstrate that high sales volume links to high crime, even after controlling for local socio-economic status, the effects of retail businesses, and local crime trends. In addition, street segment crime trajectories were spatially clustered in a significant way. The dynamics that explain why specific types of commercial facilities link to street crime need further theoretical clarification. This is the first study demonstrating significant spatio-temporal patterning of streetblock crime trends.

Spatially concentrated renovation activity and housing appreciation in the city of Milwaukee, Wisconsin

ABSTRACTThis article examines the relationship between renovation activity and housing prices in Milwaukee, Wisconsin, and whether the spatial distribution of renovation activity matters for housing appreciation. We hypothesize that the renovation of housing units is a spatially diffusive process and that proximity to renovated properties increases sale price, even after accounting for renovations to the property sold and neighborhood characteristics. By adopting a modeling approach that incorporates hedonic and repeat sales methods, we find strong evidence that proximity to renovation activity exerts a positive influence on housing appreciation and that this effect extends further in space than previously believed. Our findings lend support to policy interventions that are geographically targeted and suggest that cultivating clusters of renovated housing can be a valuable lever for neighborhood stabilization and revitalization. Though appreciation was more likely in tracts with a higher poverty rate, an analysis of annual sales volume data suggests that displacement of owner-occupier households as a result of gentrification was not widespread during the study period. However, further research to better understand spatially concentrated renovation activity as a potential contributor to the displacement of existing residents is needed.

기상요인이 의류제품 판매량에 미치는 영향 - F/W 판매데이터(9월~익년 2월)를 근거로 -

The purpose of this study was to investigate meteorological factors` effects on clothing sales based on empirical data from a leading apparel company. The daily sales data were aggregated from “A” company`s store records for the Fall/Winter season from 2012 to 2015. Daily weather data corresponding to sales volume data were collected from the Korea Meteorological Administration. The weekend effect and meteorological factors including temperature, wind, humidity, rainfall, fine dust, sea level pressure, and sunshine hours were selected as independent variables to calculate their effects on A company`s apparel sales volume. The analysis used a SAS program including correlation analysis, t-test, and multiple-regression analysis. The study results were: First, the weekend effect was the most influential factor affecting sales volume, followed by fine dust and temperature. Second, there were significant differences in the independent variables`effects on sales volume according to the garments` classification. Third, temperature significantly affected outer garments`sales volume, while top garments` sales volume was not influenced significantly. Fourth, humidity, sea level pressure and sunshine affected sales volume partly according to the garments` item. This study can provide proof of significant relationships between meteorological factors and the sales volume of garments, which will serve well to establish better inventory strategies.