Reputation, Altruism, and the Benefits of Seller Charity in an Online Marketplace

Sales forecasting is an important when it comes to companies who are engaged in retailing, logistics, manufacturing, marketing and wholesaling. It allows companies to allocate resources efficiently, to estimate revenue of the sales and to plan strategies which are better for company’s future. In this paper, predicting product sales from a particular store is done in a way that produces better performance compared to any machine learning algorithms. The dataset used for this project is Big Mart Sales data of the 2013.Nowadays shopping malls and Supermarkets keep track of the sales data of the each and every individual item for predicting the future demand of the customer. It contains large amount of customer data and the item attributes. Further, the frequent patterns are detected by mining the data from the data warehouse. Then the data can be used for predicting the sales of the future with the help of several machine learning techniques (algorithms) for the companies like Big Mart. In this project, we propose a model using the Xgboost algorithm for predicting sales of companies like Big Mart and founded that it produces better performance compared to other existing models. An analysis of this model with other models in terms of their performance metrics is made in this project. Big Mart is an online marketplace where people can buy or sell or advertise your merchandise at low cost. The goal of the paper is to make Big Mart the shopping paradise for the buyers and a marketing solutions for the sellers as well. The ultimate aim is the complete satisfaction of the customers. The project “SUPERMARKET SALES PREDICTION” builds a predictive model and finds out the sales of each of the product at a particular store. The Big Mart use this model to under the properties of the products which plays a major role in increasing the sales. This can also be done on the basis hypothesis that should be done before looking at the data

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PENGALAMAN PENGGUNA, KEAMANAN TRANSAKSI, KEMUDAHAN PENGGUNAAN, KENYAMANAN, DAN PENGARUHNYA TERHADAP PERILAKU PEMBELIAN ONLINE SECARA IMPULSIF

RELASI JURNAL EKONOMI ◽

10.31967/relasi.v18i1.523 ◽

2022 ◽

Vol 18 (1) ◽

pp. 26-45

Author(s):

Didit Darmawan ◽

Arif Rachman Putra

Keyword(s):

Linear Regression Analysis ◽

Sampling Technique ◽

Multiple Linear Regression Analysis ◽

Ease Of Use ◽

Buying Behavior ◽

Online Purchases ◽

Online Marketplace ◽

Impulsive Buying ◽

Transaction Security ◽

Online Buying

In Indonesia, online shopping has become a trend and transactions have increased drastically, marked by the development of business players involved in the online marketplace industry, one of which is Lazada, which is the top marketplace in Indonesia. Lazada is an online product buying and selling application that offers a variety of products and uses the internet and social media as a forum for interactive two-way interactions with its users. Product bids, attractive prices and availability of information can lead to impulsive buying behavior. The impulse to buy impulsively is described as a complex, sudden, pleasant purchase and the decision-making process occurs instantaneously without thinking of any other considerations. This study has the main objective of identifying the effect of user experience, transaction security, ease of use, convenience on impulsive online buying behavior aimed at the Lazada marketplace. The population in this study are consumers who have made online purchases at Lazada. The sampling technique used is non-probability sampling, with a purposive sampling method with the following sample criteria: consumers who have made online Lazada purchases more than once, and aged over 17 years to 50 years. Respondents came from the city of Sidoarjo and totaled 120 people. Multiple linear regression analysis is an analytical tool used in this study. The t test is to prove the research hypothesis which previously carried out the reliability test. From the results of the analysis of the research results, it is found that experience, safety, convenience and comfort have a significant influence on impulsive buying behavior at Lazada. The experience variable is a variable that has a dominant effect. Keywords: experience, security, ease of use, enjoyment, impulsive buying behavior.

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Chilling Effects: The Communications Decency Act and the Online Marketplace of Ideas

SSRN Electronic Journal ◽

10.2139/ssrn.1101910 ◽

2008 ◽

Author(s):

Anthony Michael Ciolli

Keyword(s):

Marketplace Of Ideas ◽

Online Marketplace

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ANALYSIS AND DESIGN OF Q-STORE MARKETPLACE CASE STUDY OF TEMBILAHAN

JURNAL PERANGKAT LUNAK ◽

10.32520/jupel.v2i1.873 ◽

2020 ◽

Vol 2 (1) ◽

pp. 15-28

Author(s):

Irwandi Rizki Putra ◽

Muh. Rasyid Ridha

Keyword(s):

Technological Development ◽

Human Life ◽

Unified Modeling Language ◽

Business World ◽

Unified Modeling ◽

The Public ◽

Analysis And Design ◽

Online Marketplace ◽

The Times

Along with the times, technology and information are developing rapidly in various sectors in terms of human life. In the business world, technological development is very helpful in many ways. The phenomenon that occurs at this time is the increasingly widespread competition in the business world, especially in the field of marketplace in getting consumers to the emergence of various online marketplace sites. So far, Tembilahan online shop business is only known through social media such as Facebook, Whatsapp and Instagram or verbally to the public. Therefore, researchers are interested in taking a title, namely Marketpleace Q-Store Market Analysis and planning. Tembilahan Case Study aims to become a media promotion, and can make it easier for people to find goods that they want. In designing this Marketplace, the analysis used is PIECES and UML (Unified Modeling Language) as modeling and using the Framework code igniter to facilitate researchers in building systems. With the implementation of the Marketplace Q-Store, it provides a platform for seller to market their products.

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