Ido Millet

On the relativity of relative measures - accommodating both rank preservation and rank reversals in the AHP

Abstract The analytic hierarchy process (AHP) has been criticized for allowing the introduction of new alternatives to cause rank reversals among existing alternatives. While in many cases this is a perfectly valid phenomenon there are also many cases where rank should be preserved. To address both contingencies the AHP now supports two types of synthesis procedures – one that preserves rank and one that does not. This paper proposes guidelines for the selection of one synthesis mode over the other. It also proposes several modifications to software implementations of the AHP to better support both synthesis modes and to reduce user stress over the choice.

The Effectiveness of Alternative Preference Elicitation Methods in the Analytic Hierarchy Process

This study compares alternative preference elicitation methods that are currently available in software implementations of the analytic hierarchy process. For the simple problem used in this study, the elicitation methods may be sorted from least to most accurate as follows: (1) direct estimation, (2) graphical multiple bars, (3) graphical pairwise, (4) numeric pairwise and (5) verbal pairwise. However, the most accurate methods are not the easiest to use. Furthermore, actual accuracy differed substantially from users’ perceptions, indicating a need to assist the users in the selection of an appropriate elicitation method.

Incorporating negative values into the analytic hierarchy process

This paper describes why and how ratio scaled multiple criteria analysis techniques, such as the Analytic Hierarchy Process (AHP), should allow for a subtraction mechanism whereby negative preference (aversion) is combined with positive preference. The main contribution of the paper is a demonstration of how the current imposition of a strictly positive additive value structure can lead to incorrect preference ratios and even incorrect ranking of alternatives. The proposed preference elicitation and computation method solves these problems in a simple and intuitive manner. Scope and purpose: We focus in this paper on common cases where the AHP is used to evaluate alternatives in light of multiple criteria and where at least some of the considerations involve negative rather than positive effects from the point of view of the decision maker. The main objective is to correct how such negative effects are evaluated within the AHP.

A conceptual research framework for analyzing online auctions in a B2B environment

The rapid growth of online auctions underscores the need to analyze the mechanism of online auctions and to establish a theoretical research framework based on the business models adopted by successful organizations. While the theoretical and empirical research bases for traditional auctions are well established, current understanding of online auctions is still very limited. A broad conceptual model is developed that can form the basis for future research in online auctions. A review of prior research and use systems theory and empirical analysis is presented to identify the potential antecedents to online auction success. Then dimensions of the input, process, and output factors are discussed to develop the conceptual model. The conceptual model provides an impetus and direction for future research into online auctions, taking advantage of existing tradition but also forming the basis for the development and testing of research hypotheses that will expand the frontiers of knowledge in online auctions.

Technical note: a proposal to simplify data flow diagrams

This technical note presents an adaptation of the data flow diagram (DFD) technique whereby each data store symbol represents a database rather than a single table. It is conjectured that this modification makes DFDs easier to create, understand, and maintain. It also reduces an overlap with the entity-relationship diagram technique by curtailing graphical manifestations of the data model in the DFD.

Data Flow Diagrams vs. Use Cases – Student Perceptions

Data flow diagrams (DFD) and Use Cases are two popular methodologies in teaching as well as in practice. We recently used both methodologies in teaching eight sections of a required systems analysis course. Questionnaire results indicate that students perceive these methodologies as equally easy to understand and use. Students believe that data flow diagrams are better at communicating with users and programmers.

Normalization on the fly

Abstract This paper describes a universal technique for data retrieval from a database file afflicted with repeating groups. The procedure relies on a generic “repeater” table which is joined to the unnormalized table. Though the physical data model may violate first normal form, the proposed technique produces a data view that overcomes that violation. The importance of this technique to the design and use of databases is demonstrated through an actual case study.

The relationship between grading leniency and grading reliability

ABSTRACT Grading reliability for a class can be measured as the correlation between the students’ grade point average (GPA) and the grades they received in that class. Grading leniency can be measured as the difference between the average grade for the class and the students’ average GPA. Data from more than fifty-thousand course sections show that lenient grading is associated with lower grading reliability. This association is particularly strong among course sections with lenient grading. Although grading leniency may be a symptom rather than a cause of low-grading reliability, reducing grading leniency may lead to improved grading reliability.

Vintage Analytics and Data Warehouse Design

Vintage Analytics is a useful technique for a variety of domains where performance depends on experience or age. However, this technique might be underutilized due to lack of awareness and due to difficulties in data preparation. This paper provides examples of Vintage Analytics, including one detailed scenario demonstrating benefits and typical challenges in the context of a sales database. It then proposes data warehouse design guidelines to address these difficulties.

Electronic Reverse Auctions - Success Metrics & Dynamics

This paper describes an on-going study analyzing thousands of electronic procurement auctions conducted by a large multinational firm. We describe the challenges of developing metrics for auction success and auction dynamics and how these metrics improve our ability to model, understand, and manage this domain. Since we are in the initial stages of our study and since many of our findings are confidential, this paper is limited to describing the metrics and the relationships investigated between supplier experience, supplier participation levels, late bidding behavior, and electronic reverse auction success. By the time of the presentation, we expect to obtain permission to reveal more details about our findings.