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Globalization of markets is changing the structure of business enterprises and hence the need for and design of computerized decision support systems. Trying to understand how decision support systems can and should evolve in a global business environment is difficult, but this article draws on current best practices, examples of deployments of available technology and trends to make some sense of the problem. Six deployment issues are examined for the five broad categories of decision support systems. The need for further research is apparent given the inadequacy of our current knowledge.

Decision support systems (DSS) are computer-based information systems which support unstructured or semi-structured managerial decisions in organizations. While it is yet to be recognized on a wide scale, DSS have become extremely important in today’s world. Many reengineering exercises are actually built around DSS. A knowledge management infrastructure often fails as organizations cannot derive support for specific decisions from it. DSS are generally aimed at reducing the unstructuredness in a decision situation. A decision situation consists of the decision itself, the decision maker and the organizational environment. An attempt at developing a DSS essentially involves an attempt at reducing unstructuredness in the decision situation. This paper presents a framework which would allow decision analysts to identify such specific sources of unstructuredness at a much more refined level than the analysis available in the literature today.

Much of IS literature suggests that various factors play pivotal roles in the implementation of an information system; however, there has been little empirical research about the factors impacting the implementation of business intelligence (BI) systems, particularly in engineering asset management organizations. There is an imperative need for a critical success factors (CSFs) approach to enable BI stakeholders to focus on the key issues of implementing BI systems. The authors conducted in-depth interviews with 15 BI practitioners of engineering asset management domain to identify factors critical for successful implementation of BI systems. Based on the findings, this study identifies ten CSFs that are crucial for implementing BI systems. This paper presents and discusses the findings, as well as puts forward recommendations for further research. This paper will be of particular interest to those researchers and practitioners who are studying, providing consultancies, planning or implementing BI systems.

Our research addresses issues of design and implementation of a framework and architecture for distributed decision making. While decision support technologies have been studied for a number of years the emergence of new standards and internet technologies provides us with an opportunity to address current problems in distributed and collaborative decision making. This class of problems has become increasingly relevant with collaborative business models such as supply and demand chains and e-business. In particular, the increasing global nature of organizational work involves collaboration across national boundaries. This has become a common business model and technology support for such activity is the focus of our work. In this paper we discuss the design of a generator that supports distributed decision making. We do this by leveraging emerging standards and technologies like Web Services, SOAP, and WSDL. Features such as ad-hoc integration, location independence and platform independence are supported in a manner that addresses independence, flexibility, interoperability, and workflow management. We present a discussion about a design prototype and associated examples using the stock market as an application domain.

Software development is a complex iterative process, where knowledge builds as work progresses, requiring an ongoing awareness by all participants of the changing definitions and relationships in the development effort. This has resulted decentralized decision making, where knowledge workers distributed across development centers are involved in making or breaking decisions. Outsourcers who develop for overseas clients have realized the need for some measures of control to manage distributed project tasks, while at the same time motivating their knowledge workers. A study of how knowledge capital is managed in a decentralized and distributed environment during the offshore software development processes forms the basis of this study. The issues are illustrated using two case studies of offshore outsourcers in New Zealand, an’ up and coming’ outsourcing nation. The study reveals that both firms emphasize monitoring and management of knowledge transfer processes, but also raises questions about the future for New Zealand outsourcers.

Recent research has suggested that groups do not exchange information effectively. This is particularly true of groups using computer-mediated communication systems (CMCS). However, generalizing the findings of these studies to real groups is difficult because they used groups and/or the groups did not have experience with the CMCS and were working on novel tasks. In this study face-to-face groups and groups using two types of CMCS completed three information exchange tasks. Information exchange performance and relational links were collected for each task. The results suggest that CMCS groups are not able to exchange information as effectively as face-to-face groups, even as they become familiar with the task and CMCS. In addition, although relational links were slightly related to information exchange performance, they were not as important as communication mode in explaining differences in information exchange performance.

Given the prevalent use of email, intelligent decisions need to be made regarding how best to manage email workloads. The email Strategy Investigation Model (eSIM) is a decision support system with this aim in mind. eSIM provides an analysis of the effects of different email processing strategies. The strategy of continuously monitoring email messages is modeled along with alternative strategies that attempt to control the interruptive nature of email while allowing for appropriate processing of email both with and without the use of key word alarm triggers. Simulation is used to model different arrival patterns of email and the flow of the knowledge worker’s focus of attention. A user of eSIM can compare various email processing strategies in deciding how best to manage his or her specific email challenges. This paper describes the eSIM decision support system in detail and provides an example of its use.

Many business consultants and strategy theorists consider Knowledge Management (KM) critical to the success of an organization. While a few empirical studies have investigated the relationships among KM capability and various measures of performance, it is still not known what KM capabilities actually affect organization performance. Also, some research has examined contingency factors related to KM and performance, but industry type has not been examined as a possible moderator. This study explored two major questions: (1) Do KM capabilities impact perceived organization performance? and (2) Do KM capabilities have different effects in different industries? The results indicate that activities for knowledge documentation, acquisition and creation positively impact business performance and that the type of industry moderates the relationships. From a resource-based and knowledge-based view of the firm, the results indicate that in some circumstances KM creates a capability that results in improved performance. In general, the results help understand the complex role of knowledge management capabilities in firms.

The evaluation of investments in information systems (IS) is usually based on conflicting criteria applied to the available alternatives, and the results are aggregated into a single ranking. The aggregation process is regularly complicated and biased through the usage of criteria weights. This article simply suggests avoiding the weighting process, and alternatively relies on a set of multiple social choice methods. This work investigates various methods of social choice voting rules for aggregation and the properties of the results they deliver in typical IS decisions. Results are compared with the outcome of traditional multiple attribute decision making, taking into account case study and simulation data. The results support our notion that weighting criteria in the context of complex IS investment appraisals does not provide a different or more comprehensive outcome than the less demanding social choice rule set applied.

Individual decision making determines critical outcomes for organizations in various domains including information security, where the increase of security incidents is causing great concern to organizations. Information security awareness programs are an important approach towards educating users to prevent such incidents. However, it is unclear how to effectively design security programs and messages such that they can inform and change user behavior. This paper attempts to investigate this problem by studying the effects of security message characteristics on users, using the decision-making theory of elaboration likelihood. A 2×2 factorial design experiment was conducted to determine the influence of message repetition and message comprehensibility on user’s elaboration likelihood towards a security message. Our findings indicate that message repetition enhances elaboration likelihood of users. Message comprehensibility interacts with message repetition in determining elaboration likelihood. The results have implications for designing effective security messages and for decision support systems for this purpose.