scholarly journals Sentiment Analysis through Big Data in online Retail Industry: A Conceptual Quantitative Study on linkage of Big-Data and Assortment Proactive of Online Retailers

2020 ◽  
Vol 3 (2) ◽  
pp. 16
Author(s):  
Muhammad Faisal Sultan ◽  
Mehwish Jabeen ◽  
Muhammad Adeel Mannan
Keyword(s):  
Big Data ◽  
Sentiment Analysis ◽  
Recent Trend ◽  
Retail Sector ◽  
Online Retail ◽  
Online Retailers ◽  
Data Scientist ◽  
Online Stores ◽  
Quota Sampling ◽  
The Impact

Big-Data is the recent trend in data sciences prevailing all over the globe. The tool aids significantly in optimization of knowledge and has predominant use in optimization of knowledge and productivity. However, there is lack of understanding of concept and its application in Pakistan as indicated by Gallup Pakistan (2018) and stream of data is going to be doubled in two years’ time Tankard (2012). Therefore, there is a definite need of research which optimizes understanding associated with technology and its application from the context of Pakistan. Hence considering the application of big-data in retail sector this study aims to explore the impact of sentiment analysis through relating impact of big-data with effective assortment s of online stores. Although data has been collected from IT experts associated with online retail sector via quota sampling and SMART-PLS has been incorporated for the purpose of analysis. Results of the study highlights that big-data is perceived as the major tool for the betterment of assortment in online retail stores although data scientist and their applicability might diminish the impact of the use of big-data.

Payment Methods and Purchase Intention from Online Stores

2016 ◽  
Vol 12 (2) ◽  
pp. 31-44 ◽  
Author(s):  
Rasha Abu-Shamaa ◽  
Emad Abu-Shanab ◽  
Rawan Khasawneh
Keyword(s):  
Technology Acceptance ◽  
Purchase Intention ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Retail Sector ◽  
Payment Method ◽  
Perceived Ease Of Use ◽  
Online Retail ◽  
Payment Methods ◽  
Online Stores

Online retail stores are a new booming phenomenon in the Arab world. Recent years witnessed a significant increase in the number of Arabic online stores launched for different kinds of products and services. Stores offer grocery products, fashion and life style items, and electronics and technology devices. Regardless of the growing investments in the Arabic online retail sector, Arabic consumers are still doubtful about online shopping. This research investigated the factors affecting Jordanians' purchase intentions from online stores by extending the technology acceptance model (TAM) to include payment method. The model included payment method (PM), perceived ease of use (PEOU) and perceived usefulness (PU), as direct predictors of the intention to use online stores and moderated by consumers' level of trust of such factors. Results indicated that TAM predictors, and payment methods do affect consumers' intention to purchase online. However, PM and PEOU relationships with the intention to shop online are the only relationships moderated by trust.

scholarly journals Long-Term Discounting Frameworks: Insights from Multiple Experiments

2020 ◽  
pp. 84-100
Author(s):  
H. R. Ganesh ◽  
P. S. Aithal ◽  
P. Kirubadevi
Keyword(s):  
Competitive Advantage ◽  
Online Retailing ◽  
Sales Promotions ◽  
Online Retailers ◽  
Brick And Mortar ◽  
Consumer Perspective ◽  
Key Drivers ◽  
Online Stores ◽  
The Impact

Ever since the online retailing format has emerged in India, consumers now have wider options available for them to buy a product at a discounted price and notably, as online stores in India are following the product discounting as one of the key drivers for consumer acquisition, consumers’ perspective towards discount at brick-and-mortar store has changed.This change in consumers’ perspective has put the majority of brick-and-mortar retailers in India into a quandary and they are losing out their market share slowly to online retailers. In this research which is based on recommendations of empirical research previously carried out on the impact of changes in retailer and consumer perspective towards discount post emergence of online stores in India, we have carried out multiple experiments on multiple long-term discounting frameworks to investigate and recommend brick-and-mortar retailers on ideal(a) frameworks, (b) duration, (c) types, (d) assortment coverage, and (e) advertising techniques for long-term discounting strategies to enable brick-and-mortar retailers to design appropriate sales promotions to gain a competitive advantage over online retailing on the discount component.

The Impact of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment

2019 ◽  
Vol 56 (6) ◽  
pp. 944-959 ◽  
Author(s):  
Donald Ngwe ◽  
Kris Johnson Ferreira ◽  
Thales Teixeira
Keyword(s):  
Price Discrimination ◽  
Field Experiments ◽  
Search Costs ◽  
Shopping Behavior ◽  
Search Frictions ◽  
Transaction Data ◽  
Online Retailers ◽  
Online Stores ◽  
Online Shopping Behavior ◽  
The Impact

Many online stores are designed such that shoppers can easily access any available discounted products. The authors propose that deliberately increasing search frictions by placing obstacles to locating discounted items can improve online retailers’ margins and even increase conversion. The authors demonstrate this using a simple theoretical framework that suggests inducing consumers to inspect higher-priced items first may simultaneously increase the average price of items sold and the overall expected purchase probability by inducing consumers to search more products. The authors test and confirm these predictions in a series of field experiments conducted with a dominant online fashion and apparel retailer. Furthermore, using information in historical transaction data about each consumer, the authors demonstrate that price-sensitive shoppers are more likely to willingly incur search costs when locating discounted items. Our results show that increasing search frictions can be used as a self-selecting price discrimination tool to match high discounts with price-sensitive consumers and full-priced offerings with price-insensitive consumers.

scholarly journals The Impact of Big Data Quality on Sentiment Analysis Approaches

2019 ◽  
Vol 160 ◽  
pp. 803-810
Author(s):  
Imane El Alaoui ◽  
Youssef Gahi
Keyword(s):  
Big Data ◽  
Data Quality ◽  
Sentiment Analysis ◽  
The Impact

Using DEMATEL to Build Decision Model of Online Reputation Management for Improving the Services of Marketing

2016 ◽  
pp. 127-146
Author(s):  
Ashutosh Yadav ◽  
Anil Kumar ◽  
Manoj Kumar Dash
Keyword(s):  
Online Communication ◽  
Online Marketing ◽  
Reputation Management ◽  
Social Aspect ◽  
Online Retail ◽  
Online Retailers ◽  
Marketing Data ◽  
Online Reputation ◽  
Post Purchase ◽  
The Impact

Online Reputation Management (ORM) is very important factor for any company in online retail industry but very little amount of work has been done by the researchers in this context. Taking into consideration online reputation, reputation management, online communication, social aspect, online ranking, incentives and post purchase service, this study utilised DEMATEL (Decision-Making Trial and Evaluation Laboratory) build an Influence Network Relation Map (INRM) model of these Online Reputation Management's factors for improving the online services of marketing. Data is collected through structured questionnaire by survey of experts. The results showed that online reputation is the most important factors followed by reputation management and social aspect is least important according given experts' opinions. The study also found out the impact within the factors and divided all factors into two groups i.e. cause group and effect group. The output of the study can help online retailers to make their online marketing strategies more effective to target and segmentation their customers.

Do Consumer Perceptions of Tanking Impact Attendance at National Basketball Association Games? A Sentiment Analysis Approach

2021 ◽  
pp. 1-12
Author(s):  
Hua Gong ◽  
Nicholas M. Watanabe ◽  
Brian P. Soebbing ◽  
Matthew T. Brown ◽  
Mark S. Nagel
Keyword(s):  
Big Data ◽  
Sentiment Analysis ◽  
Sport Management ◽  
Consumer Perceptions ◽  
National Basketball Association ◽  
Management Research ◽  
Home Team ◽  
The Many ◽  
The Impact ◽  
Game Attendance

The use of big data in sport and sport management research is increasing in popularity. Prior research generally includes one of the many characteristics of big data, such as volume or velocity. The present study presents big data in a multidimensional lens by considering the use of sentiment analysis. Specifically focusing on the phenomenon of tanking, the purposeful underperformance in sport competitions, the present study considers the impact that consumers’ sentiment regarding tanking has on game attendance in the National Basketball Association. Collecting social media posts for each National Basketball Association team, the authors create an algorithm to measure the volume and sentiment of consumer discussions related to tanking. These measures are included in a predictive model for National Basketball Association home game attendance between the 2013–2014 and 2017–2018 seasons. Our results find that the volume of discussions for the home team and sentiment toward tanking by the away team impact game attendance.

scholarly journals Perceived Usefulness of Big-Data for Store Layout: Evidence for Organized Retailers of Karachi

2021 ◽  
Vol 4 (2) ◽  
pp. 18
Author(s):  
Mehwish Jabeen ◽  
Muhammad Faisal Sultan ◽  
Muhammad Adeel Mannan
Keyword(s):  
Big Data ◽  
Emerging Markets ◽  
Perceived Usefulness ◽  
Retail Industry ◽  
Retail Sector ◽  
The Real ◽  
Societal Benefits ◽  
Quota Sampling ◽  
The One ◽  
Selection Of

Big-Data is one of the most useful technologies available nowadays to understand behaviorsand patterns. However, in addition to its societal benefits technology might also be used bypractitioners in industrial settings. The Retail industry is also treated as the one which might receive major benefits from the use of Big-Data and therefore this study is purposively associated with implications of Big-Data for the retail sector. The Study uses store layout as the dependent variable as it has the most influence on purchase as the real purpose of Big-Data is to analyze behavior and patterns, therefore, the selection of variable is legitimate. However, the technology is not well-known in emerging markets like Pakistan therefore study is linked with quota sampling and uses SMART-PLS to analyze results. Results indicated that Big-Data was perceived as the potent tool for operations of the organized retail sector of Karachi.

The Impact of Committing to Customer Orders in Online Retail

2020 ◽  
Author(s):  
Gonçalo Figueira ◽  
Willem van Jaarsveld ◽  
Pedro Amorim ◽  
Jan C. Fransoo
Keyword(s):  
Online Retail ◽  
The Impact ◽  
Customer Orders
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