International Journal of Information Technology & Decision Making

The research topics of the 39 papers published in the International Journal of Information Technology and Decision Making (IT&DM) in 2009 can be classified into three major directions: decision support, multiple criteria decision making, and data mining and risk analysis. The Editor-in-Chief, on behalf of the editorial board and advisory board, highlights the key ideas of these contributions. The seven papers in first issue of 2010 IT&DM are also introduced.

Set-valued information systems are generalized models of single-valued information systems. Its semantic interpretation can be classified into two categories: disjunctive and conjunctive. We focus on the former in this paper. By introducing four types of dominance relations to the disjunctive set-valued information systems, we establish a dominance-based rough sets approach, which is mainly based on the substitution of the indiscernibility relation by the dominance relations. Furthermore, we develop a new approach to sorting for objects in disjunctive set-valued ordered information systems, which is based on the dominance class of an object induced by a dominance relation. Finally, we propose criterion reductions of disjunctive set-valued ordered information systems that eliminate only those information that are not essential from the ordering of objects. The approaches show how to simplify a disjunctive set-valued ordered information system. Throughout this paper, we establish in detail the interrelationships among the four types of dominance relations, which include corresponding dominance classes, rough sets approaches, sorting for objects and criterion reductions. These results give a kind of feasible approaches to intelligent decision making in disjunctive set-valued ordered information systems.

The purpose of this study is to examine the effects of operational and strategic information exchange on supply chain performance and the moderating role of information quality in relation to both operational and strategic information exchange. The study was conducted using manufacturing companies located in the Northern region of Malaysia. Hierarchical multiple regressions were applied to test the hypotheses developed for the study. It was found that operational and strategic information exchange is significantly related to supply chain performance. The impact of strategic information exchange is greater as opposed to operational information exchange. Information quality does not moderate the relationship between both operational and strategic information exchange and supply chain performance. Nonetheless, this study provides evidence that both strategic information exchange and operational information exchange are required to enhance supply chain performance. As such supply chain partners should effectively exchange strategic information as the impact is greater on performance.

This paper presents NexClass, a Decision Support System (DSS) which supports classification of alternatives into predefined non-ordered categories according to their performance on evaluation criteria and implements a novel classification algorithm based on multicriteria analysis and outranking relations. More detailed, assignment to classes is based on the concept of non-exclusivity, which defines at what degree an alternative can be included in a specific category. For each category, a threshold is defined by the decision maker, which indicates its limit with respect to the evaluation criteria. Alternatives are next evaluated according to the criteria and non-excluding degrees are calculated for each category. Finally, an alternative is assigned to the category for which non-excluding degree gets the lowest value. NexClass DSS implements the above classification algorithm, providing a user-friendly interface, which supports decision makers to formulate and solve classification problems. In addition to the methodology and the DSS, we present a real world application at a classification problem in banking environment. Our findings derived from evaluation experiments in the banking environment provide valid evidence that the proposed methodology and the DSS effectively support decision makers in classification decisions.

Sophisticated mobile wireless, net-connected devices are allowing people who do not know each other to cluster temporarily around information of mutual interest. Rheingold characterized the sociology of this brave new world of social medium as a world of "ad-hocracy". This paper aims to explore a force that can drive context-sensitive companionable relationships or activities in the "ad-hocracy" world of wireless ad-hoc networks and presents a contextualized micro-pricing mechanism for content services operating in the environment of wireless ad-hoc networks. This is a novel effective pricing mechanism that involves both value-based pricing and contextualized consideration of perishability (in terms of time, location, and urgency). This mechanism is the first attempt in adding the contextual element into pricing and is believed to encourage further exploration of pricing methods in the "ad-hocracy" world. The notion of contextualized micro-pricing is believed not only to improve mobile peers' willingness to furnish differentiated services but also to enhance the distribution of the service resources on the social medium of the wireless ad-hoc network environments.

There is an original software package offered for statistical processing of experimental information. It is designated for users who are not professionals in the field of applied statistics and computer science. The package is universal, simple and convenient for understanding and application. The problems and the algorithms realized in the package, the features and the opportunities of their application are described. Those features which distinguish favorably this package from other similar products are emphasized. The examples showing the efficiency of the algorithms realized in the package are cited. Serviceability of the suggested package was tested in various modes at solving the problems from different fields of knowledge. The obtained results justify the stability and the reliability of algorithms and the high accuracy of the calculated values.

This study examines the complex and evolutionary nature of supply network configuration. Taking a bottom-up approach, we examine how supply network configuration at the macro-level evolves as a result of individual retailers' dynamic choice of procurement strategies at the micro-level. Employing agent-based modeling, we focus on the effects of switch cost and distributors' ordering policy on the evolution of supply network configuration. Our results show that (1) supply networks tend to evolve into a set of separate supply chains when switch cost is high and into an integrated network when switch cost is low, (2) a responsive ordering policy adopted by distributors is more conducive to the integrated network configuration than a non-responsive policy, and (3) lack of coordination among retailers in their dynamic choice of procurement strategies hurts not only the overall system performance, but also retailers themselves. More importantly, our study demonstrates the capabilities of agent-based modeling as a methodology for researching complex supply network issues.

The Analytic Hierarchy Process (AHP) uses pairwise comparison to evaluate alternatives' advantages to a certain criterion. For decision-making problem with many different criteria and alternatives, pairwise comparison causes a prolonged decision-making period and rises fatigue in decision-makers' mentality. A question of practical value is if there exists a way to reduce judgment number and what influence the reduction will have on the overall evaluation of alternative ratings. To answer this question, we introduce scale error and judgment error into AHP judgment matrix. By expanding the scales defined in the AHP, scale error is eliminated. Taking judgment error as random variable, a new estimator to calculate priority vector is presented. In the end, an example is proved to show lowering judgment number will increase the probability of larger errors appearing in priority vector computation.