This paper addresses four interconnected topics in information technology and business. It begins with an analysis of Dell.com's e-commerce architecture, examining its pre-purchase, purchase, and post-purchase elements across four market segments, and assessing the site's convenience and security features. It then categorizes eight business problems by the most suitable intelligent system type — expert system, decision support system, or advanced AI — with justifications for each choice. A security memo for an online pizza chain network follows, outlining platform requirements including SaaS delivery, encryption, and partner relationship management. The paper concludes with a review of research on Internet auction fraud, exploring how computerization both enables fraudulent activity and complicates detection efforts.
The site chosen for this analysis is Dell.com, which incorporates advanced e-commerce, pre-purchase, purchase, and post-purchase elements as foundational components of its design and organization. Dell has architected the site to make the process of learning about its products both convenient and role-based. On this second point, Dell has defined four key market segments — Home & Home Office, Small & Medium Business, Large Business, and Government/Education/Healthcare/Life Sciences — and gives site visitors the convenience of navigating from either a product or segment perspective.
The e-commerce strategy at Dell is based on the company's unique ability to customize personal computers, including laptops, desktops, and servers. This is a business model typically referred to as mass customization (Mylonakis, 2004). Dell is considered one of the thought leaders in this arena, specifically due to its ability to link e-commerce strategies and manufacturing execution using online product configurators (AMR Research, 2003).
The pre-purchase elements of the Dell site are designed to create loyalty and "stickiness" with prospects, as defined by Malcolm Gladwell (2006) in his articles and books on the subject. Dell's commitment to building a conversation with prospects is further evidenced by the launch of the Dell Community (Altus, 2007). The pre-purchase elements vary across each of the four segments, yet all aim to provide relevance and stickiness to visitors exploring the site.
In terms of the actual purchase elements and workflows, each begins with selecting a computing platform — laptop, desktop PC, or server — and then proceeds through product configuration software developed internally by Dell. This guided selling tool assists customers through the selection process. The workflow is well-defined and allows users to navigate back and forth between steps, enabling customers to learn as much as possible about products before committing to a purchase.
The post-purchase aspects of the site are also supported by the Dell Community, which offers message boards and interactive chat capability (Altus, 2007). In addition, Dell has increasingly made public its Premier Pages concept, which began as a service offering exclusively for the largest accounts. Premier Pages is a program in which intranet sites are created for the convenience of customers who need to resolve larger and more complex support issues across entire organizations (Business Editors & High-Tech Writers, 2000).
Dell has been criticized in the past for relying too heavily on call centers and not enough on personalized support. To address this criticism, the company has increased its use of interactive communication tools and began allowing employees to publish blogs. As a result of these factors and Dell's market position as a technology innovator, its website is highly convenient and secure at the transaction level. The use of multiple logins and layered security provides protection against fraud, as do authentication and verification technologies sourced through partnerships with CyberSource and VeriSign.
The following problems are each matched to the most suitable type of intelligent system — expert system, decision support system, or advanced AI system — with justification for each selection.
An expert system is well suited to this task. It can encode the rules and constraints of a graduate program — such as prerequisite structures, scheduling requirements, and academic milestones — and apply them to individual student circumstances to generate a personalized study plan.
A constraint-based expert system would be best suited for this application. It would need to take into account scheduling constraints, previous commitments, and periodic training requirements for post office employees. A constraint-based expert system can optimize staffing levels dynamically, whereas a purely rules-based expert system would require continuous updating to reflect the latest status and schedule of each individual employee.
An advanced AI system would be required for this application. The many attributes, factors, variables, and weightings associated with identifying potential threats must be analyzed simultaneously and in combination with one another. The complexity and speed of this analysis exceed what rule-based or decision support systems can handle effectively.
Systems from each of these categories are specifically used for stock market investing and forecasting. Decision support systems can accumulate and analyze thousands of data feeds; expert systems use constraint models to create financial scenarios; and advanced AI systems attempt to predict index values and individual stock prices by incorporating all relevant factors. Of all approaches, however, the most prevalent and successful is the use of expert systems that apply constraints to define upper and lower performance thresholds for a given stock.
An expert system works best for this task. It can quickly define job requirements and evaluate applicants against those requirements by testing skills, knowledge, and problem-solving ability in a structured and consistent manner.
An advanced AI system is best suited to this problem because it can account for the many factors contributing to power issues throughout a building, including interactions with other connected systems. The multi-variable, real-time nature of the diagnosis makes AI the most appropriate choice.
Given the complexity of this problem — which involves environmental, economic, political, and social variables interacting across long time horizons — an advanced AI system is the most appropriate approach.
While each of the system types could be applied to this task, the most effective would be an expert system capable of tracking relevant variables over time and using longitudinal analysis to determine how their combined effects have shaped the growth of a given city.
In defining a security platform to support the anticipated creation of a new online pizza chain network, the design requirements of system scalability, agility to meet customers' needs, ease of administration, and low Total Cost of Ownership (TCO) — along with the need for integration across partner pizza shops' ordering and financial reporting systems — require a platform-based rather than application-specific approach.
Because each pizza shop will maintain its own financial performance workflows as part of the chain while keeping that data confidential from other partners, single sign-on with a minimum of 128-bit encryption is required. In keeping with the platform recommendation, the concepts of partner relationship management (PRM) systems — specifically at the security level — are essential, so that each pizza shop (or partner) has its own domain and dedicated workspace within the online system.
"Security platform requirements for pizza chain IT"
"Auction fraud research and detection challenges"
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