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E-Commerce Trends and Future Analytics Tools


Affiliations
1 MBA Department, SRM University, No.1, JN Salai, Vadapalani Campus, Chennai - 600026, Tamil Nadu, India
2 CSE Department, SRM University, No.1, JN Salai, Vadapalani Campus, Chennai - 600026, Tamil Nadu, India
 

Background/Objectives: The main aim of the paper is to assess the changing trends in E - Commerce, and to explore the futuristic enabling Information technologies and tools of E - Commerce. Methods/Statistical Analysis: The study is qualitative and descriptive in nature and most of the data is based on secondary sources of survey data. Such an approach is adopted in the study as the area of research is very broad and sources of data are also spread across multiple locations. Since this research paper is based on exploratory study and secondary data, content analysis is done. Findings: From the various sources of secondary data on E - Commerce trends, it is found that Information technologies have changed the ways of doing business and disrupted many business value chains. Customer Centric approaches (product designs, pricing), collaborative web content, glocalization, big data analytics are some of the emerging paradigm shift in E Commerce. The impact of Social commerce and Ubiquitous (Mobile) commerce on E - Business and especially online purchasing cannot be ignored by both B2C and B2B categories of Business models. Broadly the emerging analytics on E - Commerce can be classified into data analytics, network analytics and mobile analytics. The market is flooded with innovative products for managing, processing, and analyzing big data. Big data has helped businesses identify events before they occur ('predictive analytics'). Also, successful adoption of advances in technology has played a key role in development of new channels for payment initiation, improved authentication and efficient processing of payment systems. Improvements/Applications: Alternate use of big data analytics includes tax evasion prevention, smart transportation, congesting pricing, smart cities, disaster warning systems, smart agro supply chains, e banking, e healthcare, energy conservation, etc.

Keywords

Analytics, Big Data, E – Commerce, Payment Systems, Social Commerce.
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  • E-Commerce Trends and Future Analytics Tools

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Authors

Premkumar Balaraman
MBA Department, SRM University, No.1, JN Salai, Vadapalani Campus, Chennai - 600026, Tamil Nadu, India
Sabarinathan Chandrasekar
CSE Department, SRM University, No.1, JN Salai, Vadapalani Campus, Chennai - 600026, Tamil Nadu, India

Abstract


Background/Objectives: The main aim of the paper is to assess the changing trends in E - Commerce, and to explore the futuristic enabling Information technologies and tools of E - Commerce. Methods/Statistical Analysis: The study is qualitative and descriptive in nature and most of the data is based on secondary sources of survey data. Such an approach is adopted in the study as the area of research is very broad and sources of data are also spread across multiple locations. Since this research paper is based on exploratory study and secondary data, content analysis is done. Findings: From the various sources of secondary data on E - Commerce trends, it is found that Information technologies have changed the ways of doing business and disrupted many business value chains. Customer Centric approaches (product designs, pricing), collaborative web content, glocalization, big data analytics are some of the emerging paradigm shift in E Commerce. The impact of Social commerce and Ubiquitous (Mobile) commerce on E - Business and especially online purchasing cannot be ignored by both B2C and B2B categories of Business models. Broadly the emerging analytics on E - Commerce can be classified into data analytics, network analytics and mobile analytics. The market is flooded with innovative products for managing, processing, and analyzing big data. Big data has helped businesses identify events before they occur ('predictive analytics'). Also, successful adoption of advances in technology has played a key role in development of new channels for payment initiation, improved authentication and efficient processing of payment systems. Improvements/Applications: Alternate use of big data analytics includes tax evasion prevention, smart transportation, congesting pricing, smart cities, disaster warning systems, smart agro supply chains, e banking, e healthcare, energy conservation, etc.

Keywords


Analytics, Big Data, E – Commerce, Payment Systems, Social Commerce.



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i32%2F129015