Current E-commerce Systems Research Articles

Impact of COVID-19 on the drivers of cash-based online transactions and consumer behaviour: evidence from a Muslim market

PurposePakistan is predominantly a cash-based economy, with consumers showing several traits ranging from low confidence on the electronic commerce security, poor access to banking, absence of widespread awareness of e-payments and other religious and psychological barriers to adopting alternatives to cash. This study aims to examine e-payment modes in Pakistan with respect to their impact on supplier and consumer behaviour before and during the pandemic times.Design/methodology/approachThe research follows a qualitative approach. Focus groups and interviews are conducted to carry out an in-depth analysis of consumer and supplier behaviour.FindingsThe findings show that customers are not satisfied with the current e-commerce system in Pakistan, whereas though producers prefer prepayments, they are forced to rely on cash on delivery. However, due to the recent COVID-19 outbreak, consumers are going cashless to avoid physical cash and observe safety protocols. To convert this temporary and enforced patronage of online transactions into a long-term and sustainable one, massive marketing and a combined effort from the government, private bodies and financial institutions is required.Research limitations/implicationsThe study was conducted using online interviews which has the drawback of connection issues, delays and lags in the connectivity, and hence may lead to miss important gestures for data analysis.Originality/valueThis research can be of benefit to online consumers and the supplier side of the online retail industry, by providing them with insight into the various factors that affect consumer behaviour towards e-commerce payment options. An understanding of the behavioural motivators of consumers will allow e-retailers in developing more marketing strategies that are effective, to improve the satisfaction level of their customers and contribute to the development of Pakistan’s e-commerce sector into a globally competitive one.

Semantic Web in the expansion of E Commerce

This study focuses on the enhancing the potential of the e-commerce websites with various Semantic web technologies. The involvement of semantic enrichment gives more meaning to the data and makes content more easily discoverable by both search engines and users. Daily thousands of people try searching for a product they are willing to buy and due to the system inefficiency, customers waste a lot of their precious time and resources and also there are a lot of problems with the current e-commerce systems. So, semantic web has certain technologies/languages specifically established for data, i.e. RDF (Resource description framework), OWL (Web ontology language) and XML, etc. which can help overcome the problems and accelerate the business to a higher level where e-commerce websites will be playing an important role.

Secure Architecture for E-commerce Websites

With the rapid growth of Information Technology(IT), the current markets are being transformed into e-markets/ecommerce.This has created a need for a secure approach toimplement e-commerce and to keep its security. To meet thisneed, Service Oriented Architecture (SOA), is one of the bestproficiencies to opt to, because it is flexible and easy to use.However, together with the advantages of SOA, there is also apossibility of unauthorized access of data, and interfering withkey data is also easy. It is therefore a challenge for someorganizations to implement secure e-commerce. This paper willexplore/highlight the significance of SOA for e-commerce andalso the issues/faults in the current e-commerce systems. Animplementation design of a secure architecture for an ecommercesystem supported by SOA has also been suggested inthis paper.

Secure Architecture for E-commerce Websites

With the rapid growth of Information Technology(IT), the current markets are being transformed into e-markets/ecommerce.This has created a need for a secure approach toimplement e-commerce and to keep its security. To meet thisneed, Service Oriented Architecture (SOA), is one of the bestproficiencies to opt to, because it is flexible and easy to use.However, together with the advantages of SOA, there is also apossibility of unauthorized access of data, and interfering withkey data is also easy. It is therefore a challenge for someorganizations to implement secure e-commerce. This paper willexplore/highlight the significance of SOA for e-commerce andalso the issues/faults in the current e-commerce systems. Animplementation design of a secure architecture for an ecommercesystem supported by SOA has also been suggested inthis paper.

Secure Architecture for E-commerce Websites

With the rapid growth of Information Technology(IT), the current markets are being transformed into e-markets/ecommerce.This has created a need for a secure approach toimplement e-commerce and to keep its security. To meet thisneed, Service Oriented Architecture (SOA), is one of the bestproficiencies to opt to, because it is flexible and easy to use.However, together with the advantages of SOA, there is also apossibility of unauthorized access of data, and interfering withkey data is also easy. It is therefore a challenge for someorganizations to implement secure e-commerce. This paper willexplore/highlight the significance of SOA for e-commerce andalso the issues/faults in the current e-commerce systems. Animplementation design of a secure architecture for an ecommercesystem supported by SOA has also been suggested inthis paper.

Semantic Web Mining in E-Commerce Websites

Semantic web is gaining interest of lot of people due to its great power. Semantic web makes the data understandable for machines. It enables machines to interpret the data published by the web in machine interpretable form. Though lots of businesses are moving towards Ecommerce websites, but there are few problems with the current ecommerce systems due to the lack of proper standards. Daily thousands of people search for the product they want to buy and due to the inefficiency of the systems it wastes lot of time and resource of the users. Semantic web has that power to overcome those problems and it can accelerate the business to further higher level where ecommerce websites are playing very important role. This paper gives the introduction of semantic web mining and its techniques and then problems of the current ecommerce systems and how those problems can be avoided using semantic web. It discusses the detailed semantic web ecommerce architecture.

Research on Network Architecture of the E-commerce Platform and Optimization of the System Performance

With the rapid development of computer technology, especially the rapid development of network technology and the acceleration of global economic integration, electronic commerce has been used more and more widely. This also puts forward a new standard for the enterprise application computer to business activities. On one hand, we should take into account the advanced nature of the electronic commerce platform, on the other hand, we should make the existing business system of the enterprise more smoothly into the new business platform. Aiming at the problem of resource bot- tleneck in current e-commerce system, the application model of grid based electronic commerce system is put forward to be based on the application background of grid technology. How to make full use of the existing software and hardware resources, to obtain the largest data processing capacity has become an important part of the electronic commerce plat- form application system. With the rapid development of economic globalization and the rapid development of Internet technology, e- commerce which is a new business model has been the world's attention and recognition. It has become the only way for the development of enterprises, which is gradually changing the business model around the world and triggering a far-reaching economic revolution. With the continuous expansion of electronic commerce, traffic system is more and more big, size of the system database is also increasing, and the property problem of the database is getting more and more prominent. Therefore, the optimization is very impor- tant to electronic commerce system database. The basic prin- ciple of system performance optimization is: access to the required data through the least possible disk access. To evaluate the database performance, in the database before and after the adjustment of the evaluation indexes should be compared, including the trade-off between response time and throughput, the availability of a database, the hit rate of the database, and the use efficiency of memory. It can measure the effect of adjustment measures to guide the direction of adjustment. How to use limited computer system resources for more users? How to guarantee the user's response speed and service quality? These problems can improve the service quality of the electronic commerce platform.

Data Mining in E-Commerce: A CRM Platform

Data is considered as a basic form of information that needs collection, management, mining and interpretation to create knowledge. Modern e-commerce is also vigorously developing that makes resources and services on the internet richly colorful. At the same time there are lots of fraudulent situations happening with people coming closer to the ecommerce system. This is an era where e-commerce is considered to be a killer-domain for successful mining data as it gives the apt ingredients from situation to situation. One of oldest things that e-commerce can do is customer relationship management (CRM). Businesses targeting customers has a direct link with the economy of a country as the current ecommerce system is used by people from lay man to business tycoons. The paper aims at a study on e-commerce with data mining proposing architectural model integrating an improved CRM system for handling business predictions and make strategies to enhance best customer relationship management.

Empirical Study and Model of User Acceptance for Personalized Recommendation

Personalized recommendation technology plays an important role in the current e-commerce system, but the user willingness to accept the personalized recommendation and its influencing factors need to be study. In this study, the Theory of Reasoned Action (TRA) and Technology Acceptance Model (TAM) are used to construct a user acceptance model of personalized recommendation which tested by the empirical method. The results show that perceived usefulness, perceived ease of use, subjective rules and trust tend had an impact on personalized recommendation.

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.

Networked Online Auctions: Agent Behavior and Strategic Gain

We consider a network of overlapping auctions and quantify the impact of overlap on agent behavior. Eliminating spatial and temporal constraints to connect physically apart customers, eauction mechanism has become one of the key components in current e-commerce system. One interesting aspect is that often there are multiple timely-overlapping mechanisms which form a network of information transfer. Since the signals revealed from an auction can influence the strategic space of users in the other ongoing auctions, it is crucial to view the market as a network in which overall interactions of mechanisms determine the global equilibrium. We present a taxonomic analysis on heterogeneous bidder behavior in a networked e-auction market. We classify the bidders’ participation and bidding strategy at individual mechanism level and at the market level. The outcomes of different strategies are compared in terms of the likelihood of winning and the relative surplus. We observe the outcome heavily relies on user strategies. We also examine whether heterogeneous mechanism formats having different winner/price determination rules influence bidder entry decision.

Framework for the development of a personalised recommender system with integrated web-mining functionalities

A challenge for current e-commerce systems is to improve customer satisfaction by providing instruments for the personalised offer of products. Personalised recommender systems are endowed with intelligent mechanisms to search products that users are interested in. In this paper, we integrate software engineering and web mining techniques in the development of an e-commerce recommender system capable of predicting the preferences of its users and present them a personalised catalogue. A data mining model induced by a decision tree algorithm is used to predict clients' preferences. The system also has an internationalisation automatic mechanism that facilitates the visualisation of the user's interface in different languages.