scholarly journals Market basket analysis with association rules in the retail sector using Orange. Case Study: Appliances Sales Company

2021 ◽  
Vol 24 (2) ◽  
Author(s):  
Marcos Martinez ◽  
Belén Escobar ◽  
Garcia-Diaz Maria-Elena ◽  
Diego P. Pinto-Roa
Keyword(s):  
Decision Making ◽  
Inventory Management ◽  
Association Rules ◽  
Retail Sector ◽  
New Approach ◽  
Useful Knowledge ◽  
Sales Company ◽  
Sporting Goods ◽  
Home Goods

This research is conducted to analyze the shopping basket by using association rules in the retail area, more specifically in a home goods sales company such as appliances, computer items, furniture, and sporting goods, among others. With the rise of globalization and the advancement of technology, retail companies are constantly struggling to maintain and raise their profits, as well ordering the products and services that the customer wants to obtain. In this sense, they need a new approach to identify different objectives in order to be more competitive and successful, looking for new decision-making strategies. To achieve this goal, and to obtain clear and efficient strategies, by providing large amounts of data collected in business transactions, the need arises to intelligently analyze such data in order to extract useful knowledge that will support decision-making and, an understanding of the association patterns that occur in sales-customer behavior. Predicting which product will make the most profit, products that are sold together, this type of information is of great value for storing products in inventory. Knowing when a product is out of fashion can support inventory management effectively. In this sense, this work presents the rules of association of products obtained by analyzing the data with the FPGrowth algorithm using the Orange tool.

scholarly journals New approach to decision making by multiple criteria analysis

2018 ◽  
Vol 146 ◽  
pp. 01002 ◽  
Author(s):  
Tomas Vanicek ◽  
Jana Kucerova
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Decision Support Tool ◽  
Decision Processes ◽  
Multiple Criteria ◽  
New Approach ◽  
Support Tool ◽  
Different Types ◽  
Multiple Criteria Evaluation

Many decision processes in technical and economical sciences require multiple criteria decision making. The most widely applied methods for multiple criteria evaluation of alternatives are based on the evaluation of alternatives in terms of an additive preference function. All of them require the estimation of weights of usually conflicting criteria. There are several methods how to find the weights of the criteria and how to find the evaluation of each solution in each criterion. The decision process based on simple weighted sum of values may not be the best approach in all situations. This paper contains a new approach of the evaluation of measured value set by different mathematical operators than the usually used multiple criteria evaluation methods. The approach was applied in a case study for multiple criteria evaluation. Generally, this new decision-support tool can help in various situations where different types of effects caused by a construction or reconstruction can occur. This is a very frequent situation in dealing with building defects, too.

Due diligence: Plantation Shutters®, South Africa

2017 ◽  
Vol 7 (2) ◽  
pp. 1-19
Author(s):  
Margie Sutherland ◽  
Hayley Pearson ◽  
Greg Fisher
Keyword(s):  
South Africa ◽  
Decision Making ◽  
Learning Outcomes ◽  
Subject Area ◽  
Management Competencies ◽  
Content Type ◽  
General Management ◽  
Sales Company ◽  
Decision Making Processes

Subject area Company turnaround, General Management. Study level/applicability Executive education, MBA. Case overview This is a four-part case study in which the case of a company turnaround emerges as the students work through a series of decision-making processes. In teaching the case, the students would only be given Part A to begin with, about which they need to make decisions as to what they would do, as preparation for the first part of the lecture. After that has been discussed, they are provided with the second part which tells them what in fact happened in the situation and leads them to the next decision point, and so on. The case deals with an entrepreneur hearing about a business that has gone insolvent; it then tracks the process from investigating the small manufacturing and sales company through the various stages of its subsequent remarkable turnaround to the point where the protagonist was voted Entrepreneur of the Year in South Africa. It covers the period 2007 to 2012 and includes the annual financial statements. Expected learning outcomes Following are the expected learning outcomes: an understanding of the broad range of management competencies; an understanding of how to turnaround a small organisation; and to experience group-based decision-making. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email [email protected] to request teaching notes. Subject code CSS 11: Strategy.

scholarly journals Novelty Ranking Approach with Z-Score and Fuzzy Multi- Attribute Decision Making Combination

2018 ◽  
Vol 7 (4.7) ◽  
pp. 476
Author(s):  
Basri . ◽  
Syarli .
Keyword(s):  
Decision Making ◽  
Statistical Technique ◽  
Z Score ◽  
New Approach ◽  
Score Method ◽  
Multi Attribute Decision Making ◽  
Weighted Data ◽  
Hierarchy Process ◽  
Better Than

This study aims to recommend a new approach in the ranking system by analyzing the combination of the Z-Score method and the Fuzzy Multi-Attribute Decision Making (FMADM) method. This fusion is based on the merging of the advantages of Z-Score and FMADM as a superiority method in statistical rank data processing with weighting data distribution. The lack of Z-Score in processing multi-attributes weighted data can be improved by the FMADM method. In this study, the integration of the Analytical Hierarchy Process (AHP) and Weighted Product (WP) methods was used as the FMADM method with the Z-Score statistical technique. The results of the analysis in the case study show that the integration of the Z-Score and AHP-Weighted Product (Z-WeP) methods can provide maximum results with similarities to the Z-Score results by 86%. Analysis of criterion values on alternatives also shows that Z-WeP can work better than some other of FMADM approaches.   

scholarly journals Facility Managers Can Impact the Procurement Landscape by Modifying the Technical Requirements

2020 ◽  
Vol 12 (1) ◽  
pp. 50-59
Author(s):  
Dean Kashiwagi ◽  
Joseph Kashiwagi ◽  
Jake Gunnoe
Keyword(s):  
Decision Making ◽  
New Approach ◽  
Bureaucratic Organization ◽  
Technical Requirements

A major problem for Facility Managers (FMs) is to get the procurement department to procure expert vendors. Hiring an expert is often neglected by a low-bidding vendor who seems to meet the organizations’ minimal technical requirements. A new approach has been developed and tested which changes the procurement landscape and ensures that the FM gets an expert vendor who pre-plans, identifies what they will deliver ahead of time in a simplistic fashion, and continually measures deviations as they perform their service. The new approach will automatically filter proposals that are not doable or deliverable and minimize risks that are caused by non-expert stakeholders’ decision making. Recent testing of this approach for a large bureaucratic organization led to 15% savings in cost, 50% savings in procurement time and elimination of extenuating and complex issues caused by stakeholders in a bureaucratic organization. This new approach is controlled by the FM professional. The approach eliminates major problems that procurement causes. The paper will review the case study and the method of application of this new approach.

Climate services for the retail sectors: the Filomena’s case

2021 ◽  
Author(s):  
Albert Martínez Botí ◽  
Lluís Palma ◽  
Francesc Roura ◽  
Andrea Manrique-Suñén ◽  
Nube González-Reviriego ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Retail Sector ◽  
Seasonal Forecasts ◽  
Reanalysis Dataset ◽  
Climate Services ◽  
North East ◽  
Climate Forecasts ◽  
Weather And Climate ◽  
Sporting Goods

<p>The need of filling the gap between medium-range weather (up to 10-15 days) and seasonal forecasts (3–6 months) has led to several operational weather and climate centres to include the subseasonal forecasting in their predictions. Although this kind of information is starting to be explored by some stakeholders, such as renewable energy, water management, agriculture or disaster prevention, there are still much more sectors who can exploit this information. In this contribution, we will present how this type of climate information is used by the retail sector, in particular by a well known French sporting goods retailer within their operations over Spain. Having reliable climate forecasts weeks in advance would allow to manage the stock, redistribute it along with different warehouses and take different advertising campaigns and prices policies to avoid both the extra-cost that implies keeping what is not sold and running out of products. A recent proof of the influence of climate on sporting goods sales has been evidenced by the large increase in sales of mountain and snow equipment during Filomena’s episode, which violently hit the south-west, centre and north-east of the Iberian Peninsula in January 2021. Trustworthy subseasonal forecasts could be equally useful during other times of the year to make some decisions, such as extending or shortening the summer sports season. To illustrate the potential of these types of climate predictions, a case study for the Filomena event in January 2021 is presented. The sub-seasonal NCEP-CFS v2 prediction system has been used to compute the probability of each tercile category for surface temperature (above-normal, below-normal or normal - where normal is the average over a reference period). Forecasts for weekly temperature were calibrated using as reference the ERA-5 reanalysis dataset and the regions with negative skill were masked. It is interesting to point out how the predictions issued three weeks in advance already indicated that surface temperature would be below normal over Spain.</p>

scholarly journals MULTI-CRITERIA MODEL BASED ON LINGUISTIC NEUTROSOPHIC NUMBERS: THE SELECTION OF UNMANNED AIRCRAFT

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Goran Ćirović ◽  
Dragan Pamučar ◽  
Nataša Popović-Miletić
Keyword(s):  
Decision Making ◽  
Forest Fires ◽  
Unmanned Aircraft ◽  
Decision Makers ◽  
New Approach ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Linguistic Neutrosophic Numbers ◽  
Selection Of

The paper presents a new approach in treating uncertainty and subjectivity in the decision making process based on the modification of Multi Attributive Border Approximation area Comparison (MABAC) and an Objective-Subjective (OS) model by applying linguistic neutrosophic numbers (LNN) instead of traditional numerical values. By integrating these models with linguistic neutrosophic numbers it was shown that it is possible to a significant extent to eliminate subjective qualitative assessments and assumptions by decision makers in complex decision-making conditions. On this basis, a new hybrid LNN OS-MABAC model was formed. This model was tested and validated on a case-study of the selection of optimal unmanned aircraft intended to combat forest fires.

scholarly journals AN INTRODUCTION TO PROSPECTIVE MULTIPLE ATTRIBUTE DECISION MAKING (PMADM)

2016 ◽  
Vol 22 (2) ◽  
pp. 309-326 ◽  
Author(s):  
Sarfaraz HASHEMKHANI ZOLFANI ◽  
Reza MAKNOON ◽  
Edmundas Kazimieras ZAVADSKAS
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Multiple Attribute Decision Making ◽  
Future Research ◽  
New Approach ◽  
Multiple Attribute ◽  
The Future ◽  
Science Community ◽  
Future Topics

In recent years futures science has received a great deal of attention and has gained worldwide credibility in the science community as the science of tomorrows. The countless applications of futures studies in various fields have been a major breakthrough for mankind. Undoubtedly, decision making is one of the most significant aspects of shaping the future and an integral part of any credible future research. Multiple Criteria Decision Making (MCDM) in general and Multiple Attribute Decision Making in particular (MADM), are among the most remarkable subparts of the decision making process. The most recent model developed using the MADM method is the Dynamic MADM. The model does not specifically concentrate on the future actions and approaches and remains to be fully explored. This research presents a new concept and a new approach in the MADM field which is called the Prospective Multiple Attribute Decision Making (PMADM). The PMADM model can very well cover the DMADM concept but instead chooses to focus on future topics. The study also introduces two new approaches. The first research aims to elaborate the basis of this model and then evolves to deal with the future limiters as they potentially pop up and change the course of future actions. The new model based on future limiters is separated and categorized into two sections; one of which is looked upon without the probabilities rate and the other one with the probabilities rate. This approach is deemed priceless due to its major applicability in the ranking of the MADM methods such as: TOPSIS, VIKOR, COPRAS, ARAS, WASPAS and etc. Finally, a case study with the various applications of PMADM model in WASPAS methodology is put forth and illustrated.

Towards an Intelligent OLAP System Facing Sparse Problems

2014 ◽  
Vol 6 (4) ◽  
pp. 41-57
Author(s):  
Rania Koubaa ◽  
Eya Ben Ahmed ◽  
Faiez Gargouri
Keyword(s):  
Association Rules ◽  
Low Frequency ◽  
Decision Makers ◽  
Specific Class ◽  
Data Warehouses ◽  
New Approach ◽  
Useful Knowledge ◽  
Rare Association ◽  
Log Files ◽  
Sparse Problems

Exploring intelligent data stored in data warehouses may efficiently assist the knowledge-seeker in his decision process. Such traced information related to performed analysis by decision-makers on data warehouses are stored in OLAP log files. These files contain useful knowledge about the analysts' preferences. Sometimes, some formulated queries provide no results. Such a dilemma is known as the sparsity problem. In this paper, to overcome this limitation in user-centric data warehouses, the authors focus on a specific class of preferences, namely the conflicting preferences. Indeed, a conflicting preference describes a low frequency preference stored in OLAP log files, so that it is considered as tailored to given analysts. Such preferences are characterized by their rarity. To deal with this issue, the authors introduce a new approach to discover these preferences through mining of rare association rules using a new introduced method for generating the N highest confidence rare association rules. The derived rare preferences will be used to reformulate the launched query avoiding an empty result. The carried out experiments on their built online recruitment data warehouse point out the efficiency of their approach.

scholarly journals The Optimization Problem of Product Mix and Linear Programming Applications: Case Study in the Apparel Industry

2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Gera Workie Woubante
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Inventory Management ◽  
Industrial Development ◽  
Optimization Problem ◽  
Management Decision ◽  
Product Mix ◽  
Use Of Resources ◽  
Customer Orders

Industrial development strategy is characterized by the efficient use of resources at every production stage. The analysis and efficient utilization of resources are made sustainable by effective management decision making techniques employed in the industry. A quantitative decision making tool called linear programming can be used for the optimization problem of product mix. Understanding the concept behind the optimization problem of product mix is essential to the success of the industry for meeting customer needs, determining its image, focusing on its core business, and inventory management. Apparel manufacturing firms profit mainly depends on the proper allocation and usage of available production time, material, and labor resources. This paper considers an apparel industrial unit in Ethiopia as a case study. The monthly held resources, product volume, and amount of resources used to produce each unit of product and profit per unit for each product have been collected from the company. The data gathered was used to estimate the parameters of the linear programming model. The model was solved using LINGO 16.0 software. The findings of the study show that the profit of the company can be improved by 59.84%, that is, the total profit of Birr 465,456 per month can be increased to Birr 777,877.3 per month by applying linear programming models if customer orders have to be satisfied. The profit of the company can be improved by 7.22% if the linear programming formulation does not need to consider customer orders.

scholarly journals POST-MINING OF ASSOCIATION RULES USING ONTOLOGIES AND RULE SCHEMAS

2015 ◽  
pp. 196-200
Author(s):  
R. SUBASH CHADRA BOSE ◽  
R. SIVAKUMAR
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
Association Rule Mining ◽  
Post Processing ◽  
Rule Mining ◽  
New Approach ◽  
Useful Knowledge ◽  
General Terms ◽  
User Knowledge

Knowledge discovery and databases (KDD) deals with the overall process of discovering useful knowledge from data. Data mining is a particular step in this process by applying specific algorithms for extracting hidden fact in the data. Association rule mining is one of the data mining techniques that generate a large number of rules. Several methods have been proposed in the literature to filter and prune the discovered rules to obtain only interesting rules in order to help the decision-maker in a business process. We propose a new approach to integrate user knowledge using ontologies and rule schemas at the stage of post-mining of association rules. General Terms- Lattice, Post-processing, pruning, itemset .

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