Factors Influencing Organization Success: A Case Study of Walmart
Abstract. Walmart was established by Sam Walton and beginning as a small discount retailer in Rogers, Arkansas in 1962. This paper investigates how Walmart become popular and successful in retail ...
Walmart's Acquisition of Flipkart: Emerging Paradigm of the Digital Era
At the end of 2017, Walmart had market capitalization of US$250 billion, while Amazon was valued at US$680 billion. The higher valuation was attributed to investor perception of Amazon as a robust company with technology, innovation, high potential for future, etc. In 2017, Amazon had spent US$23 billion on Research and Development.
PDF Business Model Evaluation: Quantifying Walmart's Sources of Advantage
academic papers, case studies, and books about Walmart to describe the company's business model choices over time. Second, we implement the quantitative model in order to determine the effect of Walmart's choices on its performance. The results reveal that while Walmart's business model did not change during the 36-
PDF Business Model Evaluation: Quantifying Walmart's Sources of Advantage
We apply the method to Walmart. Using evidence from annual reports, research papers, case studies, and books for the period of 1972-2008, we build a qualitative representation of Walmart's business model. We then map that representation to an analytical model that quantifies Walmart's sources of competitive advantage over a 36-year period.
The Economic Impacts of Walmart Supercenters
Our purpose is to review the economic impacts of Walmart's disruption of the food retailing industry. This review synthesizes the extant knowledge and research findings related to the economic impacts of Walmart's entry into, and subsequent domination of, food retailing in the United States and more broadly globally. The findings suggest five broad generalizations: (a) Walmart's physical ...
WalMart and Local Economic Development: A Survey
This article reviews the literature that evaluates WalMart's impacts on local economies. The authors first describe the methods used to account for potential reverse causality of WalMart's store location decisions, and then they discuss the literature assessing the company's effect on three aspects of community life: (a) retail (and nonretail) businesses, across large- and small-sized ...
Walmart's Sales Data Analysis
In this paper, we analysed the data sets of world's largest retailers, Walmart Store to determine the business drivers and predict which departments are affected by the different scenarios (such as temperature, fuel price and holidays) and their impact on sales at stores' of different locations. We have made use of Scala and Python API of ...
A Comparative Study on Forecasting of Retail Sales
fact, in this paper, we have used LightGBM, which is a tree-based gradient boosting method for Walmart sale's predictions. 3 Data Exploration In this section, we will explore the M5 forecasting (estimate the unit sales of Walmart retail goods) data provided by Walmart, which can be accessed from kaggleKaggle. 3.1 The Dataset
Omnichannel battle between Amazon and Walmart: Is the focus on delivery
1. Introduction. In the past decade, trade press and academic research in marketing has highlighted the rise of omnichannel retailing. This type of retailing involves employing multiple channels and integrating activities within and across these channels to correspond with how customers shop (Ailawadi & Farris, 2017).The Marketing Science Institute (MSI) has recognized omnichannel retailing as ...
Harvard Case Study: Global Management (Wal-Mart)
In November 2004 Wal-Mart did just that, donating $5 billion to Tsinghua ) University to establish China's first-ever institute for retailing research. Unions and Politics Wal-Mart was able to side-step any harsh critics with the reply that it was China (through the ACFTU) that mandated/conceded unionization of workers and not itself.
A Multiobjective Optimization for Clearance in Walmart ...
Walmart increased its sell-through rate (i.e., the number of units sold during the markdown period divided by its inventory at the beginning of the markdown) by 21% and reduced its costs by 7%. Benefits that Walmart accrues include demographics-based store personalization, reductions in operating costs with limited numbers of price adjustments ...
Walmart Sales Forecasting using XGBoost algorithm and Feature
Experimental results show our method achieves superior performance over the other machine learning approaches. This paper's RMSSE metric is 0.141 and 0.113 lower than Logistic regression algorithm and Ridge algorithm respectively. Moreover, this paper also research the importance ranking of features and obtain some constructive guidance.
Walmart Company Analysis
To achieve this, Walmart has focused on two main aspects which include physical expansion and gaining sufficient market share. In 2012, Walmart has allocated $ 753 for its expansion purposes. The budgetary allocation has been effected prior to entry of Target Corporation, a US based company into Canada.
The research literature on Wal-Mart: Some frowns, some smiley faces
About the most that can be said about Wal-Mart's effect on jobs is that it is small—even by the standards of counties with modest populations—which itself might be a useful point, given the current rhetoric on both sides. Firms: Much research attention is also given to Wal-Mart's supposed demolition of existing businesses in a community ...
FORECASTING of WALMART SALES using MACHINE LEARNING ALGORITHMS
The study and implementation of several ensemble classification algorithms employed on sales data, consisting of weekly retail sales numbers from different departments in Walmart retail outlets all over the United States of America, shows the best algorithm and hyperparameter values at which the best results are obtained. The ability to predict data accurately is extremely valuable in a vast ...
(PDF) Walmart store sales forecasting
National Research University Higher School of Economics Faculty of Computer Science Applied Mathematics and Information Science Walmart store sales forecasting Shafarostov Artem, Nicolich Stefan Moscow, 23 october 2016 1 Explanation of the choice of the dataset There are many reasons behind choosing this dataset: • This dataset contains 4 different types of features: binary, quantitative ...
Walmart Research Papers
This research paper provides insight into the emergence of Wal-Mart in Indian retail sector, its challenges with the existing Mom & Pop stores, evaluating Wal-Mart's existing business model, strategies to combat unorganized Indian retail sector and innovating new ideas for effective logistic systems.
COMMENTS
Abstract. Walmart was established by Sam Walton and beginning as a small discount retailer in Rogers, Arkansas in 1962. This paper investigates how Walmart become popular and successful in retail ...
At the end of 2017, Walmart had market capitalization of US$250 billion, while Amazon was valued at US$680 billion. The higher valuation was attributed to investor perception of Amazon as a robust company with technology, innovation, high potential for future, etc. In 2017, Amazon had spent US$23 billion on Research and Development.
academic papers, case studies, and books about Walmart to describe the company's business model choices over time. Second, we implement the quantitative model in order to determine the effect of Walmart's choices on its performance. The results reveal that while Walmart's business model did not change during the 36-
We apply the method to Walmart. Using evidence from annual reports, research papers, case studies, and books for the period of 1972-2008, we build a qualitative representation of Walmart's business model. We then map that representation to an analytical model that quantifies Walmart's sources of competitive advantage over a 36-year period.
Our purpose is to review the economic impacts of Walmart's disruption of the food retailing industry. This review synthesizes the extant knowledge and research findings related to the economic impacts of Walmart's entry into, and subsequent domination of, food retailing in the United States and more broadly globally. The findings suggest five broad generalizations: (a) Walmart's physical ...
This article reviews the literature that evaluates WalMart's impacts on local economies. The authors first describe the methods used to account for potential reverse causality of WalMart's store location decisions, and then they discuss the literature assessing the company's effect on three aspects of community life: (a) retail (and nonretail) businesses, across large- and small-sized ...
In this paper, we analysed the data sets of world's largest retailers, Walmart Store to determine the business drivers and predict which departments are affected by the different scenarios (such as temperature, fuel price and holidays) and their impact on sales at stores' of different locations. We have made use of Scala and Python API of ...
fact, in this paper, we have used LightGBM, which is a tree-based gradient boosting method for Walmart sale's predictions. 3 Data Exploration In this section, we will explore the M5 forecasting (estimate the unit sales of Walmart retail goods) data provided by Walmart, which can be accessed from kaggleKaggle. 3.1 The Dataset
1. Introduction. In the past decade, trade press and academic research in marketing has highlighted the rise of omnichannel retailing. This type of retailing involves employing multiple channels and integrating activities within and across these channels to correspond with how customers shop (Ailawadi & Farris, 2017).The Marketing Science Institute (MSI) has recognized omnichannel retailing as ...
In November 2004 Wal-Mart did just that, donating $5 billion to Tsinghua ) University to establish China's first-ever institute for retailing research. Unions and Politics Wal-Mart was able to side-step any harsh critics with the reply that it was China (through the ACFTU) that mandated/conceded unionization of workers and not itself.
Walmart increased its sell-through rate (i.e., the number of units sold during the markdown period divided by its inventory at the beginning of the markdown) by 21% and reduced its costs by 7%. Benefits that Walmart accrues include demographics-based store personalization, reductions in operating costs with limited numbers of price adjustments ...
Experimental results show our method achieves superior performance over the other machine learning approaches. This paper's RMSSE metric is 0.141 and 0.113 lower than Logistic regression algorithm and Ridge algorithm respectively. Moreover, this paper also research the importance ranking of features and obtain some constructive guidance.
To achieve this, Walmart has focused on two main aspects which include physical expansion and gaining sufficient market share. In 2012, Walmart has allocated $ 753 for its expansion purposes. The budgetary allocation has been effected prior to entry of Target Corporation, a US based company into Canada.
About the most that can be said about Wal-Mart's effect on jobs is that it is small—even by the standards of counties with modest populations—which itself might be a useful point, given the current rhetoric on both sides. Firms: Much research attention is also given to Wal-Mart's supposed demolition of existing businesses in a community ...
The study and implementation of several ensemble classification algorithms employed on sales data, consisting of weekly retail sales numbers from different departments in Walmart retail outlets all over the United States of America, shows the best algorithm and hyperparameter values at which the best results are obtained. The ability to predict data accurately is extremely valuable in a vast ...
National Research University Higher School of Economics Faculty of Computer Science Applied Mathematics and Information Science Walmart store sales forecasting Shafarostov Artem, Nicolich Stefan Moscow, 23 october 2016 1 Explanation of the choice of the dataset There are many reasons behind choosing this dataset: • This dataset contains 4 different types of features: binary, quantitative ...
This research paper provides insight into the emergence of Wal-Mart in Indian retail sector, its challenges with the existing Mom & Pop stores, evaluating Wal-Mart's existing business model, strategies to combat unorganized Indian retail sector and innovating new ideas for effective logistic systems.