Search results for "Commerce."
showing 10 items of 460 documents
What really causes large price changes?
2003
We study the cause of large fluctuations in prices in the London Stock Exchange. This is done at the microscopic level of individual events, where an event is the placement or cancellation of an order to buy or sell. We show that price fluctuations caused by individual market orders are essentially independent of the volume of orders. Instead, large price fluctuations are driven by liquidity fluctuations, variations in the market's ability to absorb new orders. Even for the most liquid stocks there can be substantial gaps in the order book, corresponding to a block of adjacent price levels containing no quotes. When such a gap exists next to the best price, a new order can remove the best q…
Competition and horizontal integration in maritime freight transport
2010
This paper develops a theoretical model for freight transport characterized by competition between means of transport (the road and maritime sectors), where modes are perceived as differentiated products. Competitive behavior is assumed in the road freight sector, and there are constant returns to scale. In contrast, the freight maritime sector is characterized by oligopolistic behavior, where shipping lines enjoy economies of scale. The market equilibrium where the shipping lines behave as profit maximizers, provides a first approximation to the determinants of market shares, profits, and user welfare. We then characterize the equilibrium when horizontal integration of shipping lines occur…
Simulation-Based Performance Study of e-Commerce Web Server System – Results for FIFO Scheduling
2013
The chapter concerns the issue of overloaded Web server performance evaluation using a simulation-based approach. We focus on a Business-to-Consumer (B2C) environment and consider server performance both from the perspective of computer system efficiency and e-business profitability. Results of simulation experiments for the Web server system under First-In-First-Out (FIFO) scheduling are discussed. Much attention has been paid to the analysis of the impact of a limited server system capacity on business-related performance metrics.
Analysis of Aggregated Bot and Human Traffic on E-Commerce Site
2014
A significant volume of Web traffic nowadays can be attributed to robots. Although some of them, e.g., search-engine crawlers, perform useful tasks on a website, others may be malicious and should be banned. Consequently, there is a growing need to identify bots and to characterize their behavior. This paper investigates the share of bot-generated traffic on an e-commerce site and studies differences in bots' and humans' session-based traffic by analyzing data recorded in Web server log files. Results show that both kinds of sessions reveal different characteristics, including the session duration, the number of pages visited in session, the number of requests, the volume of data transferre…
HTTP-level e-commerce data based on server access logs for an online store
2020
Abstract Web server logs have been extensively used as a source of data on the characteristics of Web traffic and users’ navigational patterns. In particular, Web bot detection and online purchase prediction using methods from artificial intelligence (AI) are currently key areas of research. However, in reality, it is hard to obtain logs from actual online stores and there is no common dataset that can be used across different studies. Moreover, there is a lack of studies exploring Web traffic over a longer period of time, due to the unavailability of long-term data from server logs. The need to develop reliable models of Web traffic, Web user navigation, and e-customer behaviour calls for …
Modeling a non-stationary bots’ arrival process at an e-commerce Web site
2017
Abstract The paper concerns the issue of modeling and generating a representative Web workload for Web server performance evaluation through simulation experiments. Web traffic analysis has been done from two decades, usually based on Web server log data. However, while the character of the overall Web traffic has been extensively studied and modeled, relatively few studies have been devoted to the analysis of Web traffic generated by Internet robots (Web bots). Moreover, the overwhelming majority of studies concern the traffic on non e-commerce websites. In this paper we address the problem of modeling a realistic arrival process of bots’ requests on an e-commerce Web server. Based on real…
Verification of Web traffic burstiness and self-similarity for multiple online stores
2017
Developing realistic Web traffic models is essential for a reliable Web server performance evaluation. Very significant Web traffic properties that have been identified so far include burstiness and self-similarity. Very few relevant studies have been devoted to e-commerce traffic, however. In this paper, we investigate burstiness and self-similarity factors for seven different online stores using their access log data. Our findings show that both features are present in all the analyzed e-commerce datasets. Furthermore, a strong correlation of the Hurst parameter with the average request arrival rate was discovered (0.94). Estimates of the Hurst parameter for the Web traffic in the online …
Practical Aspects of Log File Analysis for E-Commerce
2013
The paper concerns Web server log file analysis to discover knowledge useful for online retailers. Data for one month of the online bookstore operation was analyzed with respect to the probability of making a purchase by e-customers. Key states and characteristics of user sessions were distinguished and their relations to the session state connected with purchase confirmation were analyzed. Results allow identification of factors increasing the probability of making a purchase in a given Web store and thus, determination of user sessions which are more valuable in terms of e-business profitability. Such results may be then applied in practice, e.g. in a method for personalized or prioritize…
Web Server Support for e-Customer Loyalty through QoS Differentiation
2013
The paper deals with the problem of offering predictive service in e-commerce Web server systems under overload. Due to unpredictability of Web accesses, such systems often fail to effectively handle peak traffic, which results in long delays and incomplete transactions. As a consequence, online retailers miss an opportunity to attract new customers, retain the loyalty of regular customers, and increase profits. We propose a method for priority-based admission control and scheduling of requests at the Web server system in order to differentiate Quality of Service (QoS) with regard to user-perceived delays, i.e., Web page response times provided by the system (as opposed to HTTP request resp…
Improving the quality of e-commerce web service: what is important for the request scheduling algorithm?
2005
The paper concerns a new research area that is Quality of Web Service (QoWS). The need for QoWS is motivated by a still growing number of Internet users, by a steady development and diversification of Web services, and especially by popularization of e-commerce applications. The goal of the paper is a critical analysis of the literature concerning scheduling algorithms for e-commerce Web servers. The paper characterizes factors affecting the load of the Web servers and discusses ways of improving their efficiency. Crucial QoWS requirements of the business Web server are identified: serving requests before their individual deadlines, supporting user session integrity, supporting different cl…