Thomas W. Lauer

Building online trust through privacy practices

This study applies Mayer etxa0al. [24] trust model to an Internet context. A model is presented linking privacy policy, through trustworthiness, to online trust, and then to customers’ loyalty and their willingness to provide truthful information. The model is tested using a sample of 269 responses. The findings suggest that consumers’ trust in a company is closely linked with the perception of the company’s respect for customer privacy. Trust in turn is linked to increased customer loyalty that can be manifested through increased purchases, openness to trying new products, and willingness to participate in programs that use additional personal information.

Software project managers' risk preferences

A questionnaire was administered to 68 software project managers (SPMs). Questions were designed to test whether SPMs risky judgments were more consistent with Expected Utility Theory or Prospect Theory. Although the results were more consistent with Prospect Theory, they differed in important ways showing SPMs judgments to be less homogeneous than is assumed by either theory. These results highlight the potential importance of SPMs judgments to the outcome of software development projects.

Optimizing airline passenger prescreening systems with Bayesian decision models

The Transportation Security Agency provides airline security in the United States using a variety of measures including a computer based passenger prescreening system. This paper develops Bayesian decision models of two prescreening systems: one that places ticketed passengers into two classifications (fly and no-fly), and a three classification system that includes potential flight. Using a parameterized cost structure, and the expected monetary value decision criteria, this paper develops optimal levels of undesirable personal characteristics that should place people into the various categories. The models are explored from both the government perspective and the passengers perspective.

The bank loan approval decision from multiple perspectives

This paper develops a probability model to evaluate the predictive validity of two-way classification schemes in the context of personal credit scoring and bank loan applications. The Bayesian decision model provides a structure for identifying classification rules that lead to optimal-maximum expected payoff or minimum expected cost-classifications. Using payoffs from multiple perspectives allows identifying conditions where the various perspectives produce contradictory classifications generating either profit premiums or cost penalties depending on the perspective.

Information requirements prototyping for decision support systems

Information requirements determination for Decision Support Systems (DSS) is often inadequately handled due to premature structuring thus precluding dynamic changes in the framing of the problem by managers. A review of relevant concepts in the behavioural decision making literature is provided. Case studies from three large business organizations illustrate system problems with information requirements. The authors suggest prototyping as a more valid approach to determining information requirements.