A CATEGORIZATION AND ALGORITHM FOR DETERMINING ONLINE SHOPPING BEHAVIOR IN A B2C ECOMMERCE CONTEXT

Online shopping behavior can be classified as experiential, utilitarian, and mixed. A questionnaire administered in a laboratory setting was given to several hundred subjects to categorize them along those levels, based on a classification algorithm. The current investigation complements the existing businessto- consumer e-commerce research by defining online shopping behavior in a more complex and comprehensive way. Online shopping behavior is categorized along a ternary classification instead of the traditional binary one in the literature. With the inclusion of mixed behavior, the three-level classification portrays a more realistic representation of the complex consumer behavior over the simpler, polarized, and dichotomous grouping of experiential versus utilitarian behavior

User Interface, Multimedia Richness, and Learning Style on the World Wide Web: A Literature Review

Electronic commerce had witnessed considerable growth over the past few years and is expected to continue growing in the future. The World Wide Web is increasingly becoming an important avenue of the marketplace. However, unlike the traditional retail outlets of business, it lacks certain aspects like being physically in a store and interacting with customer sales people. A well-designed user interface can overcome some of these limitations and aid customers in their search of products and services. This paper examines user interface and the richness of a multimedia site on the World Wide Web, as well as users\u27 learning styles, in terms of the literature

Online System Identification of DC-DC Converter for RFPA

This paper describes non-parametric system identification of a DC-DC converter based on spectral analysis correlation method. The used technique identifies the open-loop characteristics of a DC-DC converter online while the unit operates in closed-loop. A digital controller is used to perform both the closed-loop control of the converter and to periodically identify the converter by injecting a pseudo-random binary perturbation. Experimental results are provided for an example buck-boost converter to demonstrate accurate identification of the converter control-to-output frequency response. Experimental results have revealed stable operation of the converter during identification while meeting severe transient response requirements. This technique is advantageous for developing wide-input range/wide-output range converters which are vital for RF power amplifiers used in space and telecommunication applications. Keywords: System Identification, Adaptive Control, DC-DC converter, RFP

Interactive Experiential ECommerce: An Experimental Study

This study explores the effects of two independent variables: navigation shopping behavior (experiential vs. utilitarian) and interactivity levels (low vs. high) on flow experience, in a laboratory experiment that is a 2 x 2 factorial in a completely randomized design. The experiment deals with two commercial web sites: an original with high interactive features and a custom-made, parallel, and fictitious site with low interactive features. The study handles one independent variable, flow experience, in terms of its sensory, affective, cognitive, behavioral, and relational dimensions, based on Schmitt\u27s (1999, 2003) definition of the user experience and in light of flow theory (Csikszentmihalyi, 1975, 1990, 2000)

Kantian Inquiring Systems: An Illustration of a Retail Organization

The Kantian inquiring system can be used as a model for learning organizations. Based on Churchman\u27s work (1971) and Courtney, Croasdell, and Paradice\u27s work (1998), this paper discusses the Kantian inquiring system and applies it to a retail organization. Kantian systems take inputs in the context of a space-time framework and theories, process the inputs using multiple models, and interpret the data in terms of the best fitting model. Accepted outputs from the system are integrated into the system\u27s fact net. The guarantor of the system is the fit between the data and the model. Recommendations are made regarding the retail organization, using guidelines from the Kantian inquiring system, to improve its operations

TOWARDS A HOLISTIC EFFICIENT STACKING ENSEMBLE INTRUSION DETECTION SYSTEM USING NEWLY GENERATED HETEROGENEOUS DATASETS

With the exponential growth of network-based applications globally, there has been a transformation in organizations\u27 business models. Furthermore, cost reduction of both computational devices and the internet have led people to become more technology dependent. Consequently, due to inordinate use of computer networks, new risks have emerged. Therefore, the process of improving the speed and accuracy of security mechanisms has become crucial.Although abundant new security tools have been developed, the rapid-growth of malicious activities continues to be a pressing issue, as their ever-evolving attacks continue to create severe threats to network security. Classical security techniquesfor instance, firewallsare used as a first line of defense against security problems but remain unable to detect internal intrusions or adequately provide security countermeasures. Thus, network administrators tend to rely predominantly on Intrusion Detection Systems to detect such network intrusive activities. Machine Learning is one of the practical approaches to intrusion detection that learns from data to differentiate between normal and malicious traffic. Although Machine Learning approaches are used frequently, an in-depth analysis of Machine Learning algorithms in the context of intrusion detection has received less attention in the literature.Moreover, adequate datasets are necessary to train and evaluate anomaly-based network intrusion detection systems. There exist a number of such datasetsas DARPA, KDDCUP, and NSL-KDDthat have been widely adopted by researchers to train and evaluate the performance of their proposed intrusion detection approaches. Based on several studies, many such datasets are outworn and unreliable to use. Furthermore, some of these datasets suffer from a lack of traffic diversity and volumes, do not cover the variety of attacks, have anonymized packet information and payload that cannot reflect the current trends, or lack feature set and metadata.This thesis provides a comprehensive analysis of some of the existing Machine Learning approaches for identifying network intrusions. Specifically, it analyzes the algorithms along various dimensionsnamely, feature selection, sensitivity to the hyper-parameter selection, and class imbalance problemsthat are inherent to intrusion detection. It also produces a new reliable dataset labeled Game Theory and Cyber Security (GTCS) that matches real-world criteria, contains normal and different classes of attacks, and reflects the current network traffic trends. The GTCS dataset is used to evaluate the performance of the different approaches, and a detailed experimental evaluation to summarize the effectiveness of each approach is presented. Finally, the thesis proposes an ensemble classifier model composed of multiple classifiers with different learning paradigms to address the issue of detection accuracy and false alarm rate in intrusion detection systems

Strategic Integration of IT and Business Service Management

BMC Software, Inc., a leading global provider of enterprise management solutions helps companies to automate their Information Technology (IT) and align it to the needs of the business, pioneered the concept of Business Service Management (BSM). This case investigates how BMC provides products and services to help IT organizations incorporate Information Technology Service Management (ITSM) and BSM into business processes. The implementation of this strategy has made BMC a leader in BSM solutions. As a result of its business strategy, between 2002 and 2007, BMC revenue increased from $1,289 to$1,580 (in millions); stock value increased from $11.50 to$36.92

An Overview of Flow Theory in Ecommerce

The present study examined flow theory in the literature and especially in ecommerce contexts: computer and online games,virtual environments, online shopping, interface design, marketing, and management. Designing for a positive userexperience has become an equally important goal of interface design in addition to usability. Thus, studying user’s flowexperience is a valuable undertaken, which will provide insights for human computer interaction and guidance to interfacedesign, including online and mobile applications. An exploratory factor analysis was conducted using Webster et al. (1993)instrument, which was administered to 310 subjects, following their experience navigating an apparel commercial web site.Based on the results of the factor analysis, three dimensions of flow emerged: control, attention focus, and cognitiveenjoyment. Implications for contributions and future research are discussed

Dell\u27s Use of CRM-SCM Integration to Dominate the PC Market

Dell is one of the most successful and profitable computer corporations in history. It has been known for its innovative customer service and product custom configuration. As it continues to grow, it is faced with the challenge of how to maintain its customer relationships and inventory management, while continuing to meet the demands and requirements of its customers. This paper will examine how Dell implements enterprise-wide computing software, which profiles and targets its customers, as well as streamlines the flow of its products throughout the supply chain. Dell\u27s collaboration with other computer software companies has allowed it to become a leader in customer relationship management (CRM) and supply-chain management (SCM). These initiatives have resulted in net revenues of between $30 and$60 million over the last five years