The paper motivates, presents, demonstrates in use, and evaluates a methodology for conducting design science (DS) research in information systems (IS). DS is of importance in a discipline oriented to the creation of successful artifacts. Several researchers have pioneered DS research in IS, yet over the past 15 years, little DS research has been done within the discipline. The lack of a methodology to serve as a commonly accepted framework for DS research and of a template for its presentation may have contributed to its slow adoption. The design science research methodology (DSRM) presented here incorporates principles, practices, and procedures required to carry out such research and meets three objectives: it is consistent with prior literature, it provides a nominal process model for doing DS research, and it provides a mental model for presenting and evaluating DS research in IS. The DS process includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication. We demonstrate and evaluate the methodology by presenting four case studies in terms of the DSRM, including cases that present the design of a database to support health assessment methods, a software reuse measure, an Internet video telephony application, and an IS planning method. The designed methodology effectively satisfies the three objectives and has the potential to help aid the acceptance of DS research in the IS discipline.

A Design Science Research Methodology for Information Systems Research

Managing trust is a problem of particular importance in peer-to-peer environments where one frequently encounters unknown agents. Existing methods for trust management, that are based on reputation, focus on the semantic properties of the trust model. They do not scale as they either rely on a central database or require to maintain global knowledge at each agent to provide data on earlier interactions. In this paper we present an approach that addresses the problem of reputation-based trust management at both the data management and the semantic level. We employ at both levels scalable data structures and algorithms that require no central control and allow to assess trust by computing an agents reputation from its former interactions with other agents. Thus the meethod can be implemented in a peer-to-peer environment and scales well for very large numbers of participants. We expect that scalable methods for trust management are an important factor, if fully decentralized peer-to-peer systems should become the platform for more serious applications than simple file exchange.

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Managing trust in a peer-2-peer information system

Despite their many advantages, e-businesses lag behind brick and mortar businesses in several fundamental respects. This paper concerns one of these: relationships based on trust and reputation. Recent studies on simple reputation systems for e-Businesses such as eBay have pointed to the importance of such rating systems for deterring moral hazard and encouraging trusting interactions. However, despite numerous studies on trust and reputation systems, few have taken studies across disciplines to provide an integrated account of these concepts and their relationships. This paper first surveys existing literatures on trust, reputation and a related concept: reciprocity. Based on sociological and biological understandings of these concepts, a computational model is proposed. This model can be implemented in a real system to consistently calculate agents' trust and reputation scores.

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A computational model of trust and reputation

Customer loyalty or repeat purchasing is critical for the survival and success of any store By focusing on online stores, this study investigates the repeat purchase intention of experienced online buyers based on means-end chain theory and prospect theory In the research model, both utilitarian value and hedonic value are hypothesised to affect repeat purchase intention positively Perceived risk is hypothesised to affect repeat purchase intention negatively and moderate the effects of utilitarian and hedonic values on repeat purchase intention Utilitarian value is proposed as a formative second-order construct formed by product offerings, product information, monetary savings and convenience Hedonic value is also proposed as a formative second-order construct formed by the six hedonic benefits that have been identified in prior research Data collected from 782 Yahoo!Kimo customers provide strong support for the research model The results indicate that both the utilitarian value and hedonic value are positively associated with buyers' repeat purchase intention A higher level of perceived risk reduces the effect of utilitarian value and increases the effect of hedonic value on repeat purchase intention Implications for theory and practice and suggestions for future research are provided

Understanding customers' repeat purchase intentions in B2C e-commerce: the roles of utilitarian value, hedonic value and perceived risk

We discuss the mechanism of multipoint relays (MPRs) to efficiently flood broadcast messages in mobile wireless networks. Multipoint relaying is a technique to reduce the number of redundant re-transmissions while diffusing a broadcast message in the network. We discuss the principle and the functioning of MPRs, and propose a heuristic to select these MPRs in a mobile wireless environment. We also analyze the complexity of this heuristic and prove that the computation of a multipoint relay set with minimal size is NP-complete. Finally, we present some simulation results to show the efficiency of multipoint relays.

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M. Stuart Lynn

Papers

Hawaii International Conference on System Sciences