This paper describes a novel algorithm and deployed system Golden Path Analyzer (GPA) that analyzes clickstreams of people trying to complete the same task on a website. It finds the shortest, successful paths taken by users - 'golden paths' - and uses these as seeds for clickstream clusters. Other users are assigned to a cluster if their clickstream is a supersequence of the golden path. The advantages of this approach are that the resulting clusters are easily comprehended, they are few in number, correspond to semantically different strategies used by the users, and jointly partition all the clickstreams. GPA's key contribution over prior work in process funnels is that by not excluding users that make diversions from the golden path, GPA is able to assign more users to fewer clusters. Another key contribution is to use actual full clickstreams as cluster seeds to which supersequences of other users are added. Golden paths correspond to complete clickstreams that are based on actual user page transitions. GPA is particularly useful for site designers to improve processes such as shopping, returns and registration. Its analyses identify which web pages cause many users to deviate from a golden path, which links distract users and the percentage of users taking each golden path. GPA has demonstrated value on more than twenty client projects in diverse industries.

In electronic commerce on the Internet, a customer can choose among several competitive suppliers, but because of the nature of the Internet, the reliability and trustworthiness of suppliers may vary significantly. The customer's goal is to maximize its utility, by minimizing the expense required to fulfil its request, and maximizing its probability of success by some deadline. To this end, the customer creates a request strategy, describing which suppliers to contact under what conditions. We describe models for representing request strategies complete with supplier reliabilities, delivery timeliness profiles, and customer deadlines. We also develop decision procedures for selecting request strategies that maximize expected utility under certain scenarios, and more efficient heuristics that approximate the optimal solution.

With the growing acceptance of the Internet as a new dissemination medium, several new and interesting challenges arise in building a digital commerce infrastructure. We discuss some of the issues that arise in building such an infrastructure. In particular, we study how one can find and pay for digital information, and how one can safeguard the information from invalid access and duplication. We use examples from our Stanford Digital Library Project to illustrate some of these problems and their potential solutions.

In a distributed environment where nodes are independently motivated, many transactions or commercial exchanges may be stymied due to a lack of trust between the participants. The addition of trusted intermediaries may facilitate some exchanges, but others are still problematic. We introduce a language for specifying these commercial exchange problems, and sequencing graphs, a formalism for determining whether a given exchange may occur We also present an algorithm for generating a feasible execution sequence of pairwise exchanges between parties (when it exists). Indemnities may be offered to facilitate previously infeasible transactions. We show when and how they enable commercial transactions.