International Journal of Information Technology & Decision Making

Advances in mobile computing and wireless communication are easing the evolution from traditional nomadic work to computer-mediated mobile collaborative work. Technology allows efficient and effective interaction among mobile users and also provides access to shared resources available to them. However, the features and capabilities of the communication infrastructure supporting these activities influence the type of coordination and collaboration employed by mobile collaborative applications in real work scenarios. Developers of these applications are typically unaware of the constraints the communication infrastructure imposes on mobile collaborative systems, because they are not easy to foresee. That leads to a high probability of communication problems in otherwise fully functional mobile collaborative support applications. This paper presents an experimental study with real devices and networks on a realistic physical environment that shows how ad hoc networks can effectively support mobile collaborative work and the practical limitations. The paper analyzes several networking issues and determines how they influence mobile collaborative work in various interaction scenarios. The paper also presents the lessons learned in the study and provides recommendations to deal with some networking issues related to real-world ad hoc networks.

This paper discusses the collaboration-conflict process: a binomial process mixing collaboration and conflict. We applied the collaboration-conflict process to Software Review Meetings, commonly adopted to verify the functional specification of software. We developed a groupware tool demonstrating the dynamics of the collaboration-conflict process in review meetings. We also provide results from an experiment with the tool in a software engineering firm. The results show that the collaboration-conflict process promotes argumentation and generates better reviews.

Problem solving through design of systems and physical artifacts is a professional activity with major financial significance. Problems in modern society tend to grow more complex and intricate, and as a response, systems grow larger. Therefore, design increasingly has also become a collaborative task. Design in itself already is challenging but collaboration adds its own challenges into the mix. In this paper, we explore the challenges of collaborative design. We approach the research problem through design science research framework; we synthesize the knowledge base and expert experiences from the environment to propositions about the challenges of collaborative design. By forging theme propositions we lay a ground for design and development of better support for collaborative design.

Cooperative work in learning environments has been shown to be a successful extension to traditional learning systems due to the great impact of cooperation on students' motivation and learning success. A recent evaluation study has confirmed our hypothesis that students who constructed their roles in a cryptographic protocol cooperatively as sequence of actions in a user interface were faster in finding a correct solution than students who worked on their own. Here, students of a cooperation group modeled a user interface collaboratively for simulation of a cryptographic protocol using interactive modeling tools on a shared touch screen. In this paper, we describe an extended approach to cooperative construction of cryptographic protocols. Using a formal language for modeling and reconfiguring user interfaces, students describe a protocol step-by-step, modeling subsequent situations and thereby actions of the protocol. The system automatically generates a colored Petri net, which is matched against an existing action logic specifying the protocol, thus allowing formal validation of the construction process. The formal approach to modeling of user interfaces covers a much broader field than a simple cryptographic protocol simulation. Still, this paper seeks at investigating the use of such a formal modeling approach in the context of cooperative learning of cryptographic protocols and to develop a basis for more complex learning scenarios.

Peculiarity oriented mining (POM), aimed at discovering peculiarity rules hidden in a dataset, is a data mining method. Peculiarity factor (PF) is one of the most important concepts in POM. In this paper, it is proved that PF can accurately characterize the peculiarity of data sampled from a normal distribution. However, for a general one-dimensional distribution, it does not have the property. A local version of PF, called LPF, is proposed to solve the difficulty. LPF can effectively describe the peculiarity of data sampled from a continuous one-dimensional distribution. Based on LPF, a framework of local peculiarity oriented mining is presented, which consists of two steps, namely, peculiar data identification and peculiar data analysis. Two algorithms for peculiar data identification and a case study of peculiar data analysis are given to make the framework practical. Experiments on several benchmark datasets show their good performance.

Recently, the number of consultative documents and research papers that discuss risk integration has grown considerably. This paper presents a comprehensive review of the work done on risk integration in the banking industry. This survey includes: (1) risk integration methods within regulatory frameworks and the banking industry; (2) challenges of risk integration; (3) risk interaction mechanisms; (4) development of risk integration approaches; (5) risk interaction results: diversification versus compounding effects; and (6) some future research topics in risk integration. We seek to understand developments in modeling risk integration, particularly in light of the global financial crisis of 2008 and important future research topics that emerge from both the literature and the banking industry.

The financial-ratio-based credit-scoring model for bond rating system requires the maximization of two conflicting objectives (i.e., the explanatory and discriminatory power, simultaneously), which had not been directly addressed in literature. The main purpose of this study is to develop a hybrid multivariate credit-scoring model that combines the principle component analysis and Fisher's discriminant analysis using the MINIMAX goal programming technique so that the maximization of the two conflicting objectives can be compromised. The performance of alternative credit-scoring models is analyzed and compared using dataset from previous studies. We find that the proposed hybrid credit-scoring model outperforms other alternative models in both explanatory and discriminatory powers.