Peter Duchessi

Collaborative e-Government: impediments and benefits of information-sharing projects in the public sector

Information-sharing projects are becoming increasingly important in both public and private organizations. Generally, organizations base their decision to move forward with an information-sharing project on the projects expected benefits such as better services, operational savings, and increased program effectiveness. Clearly, potential impediments particular to the government environment could limit the attainment of benefits, jeopardizing the projects business case and even the project itself. Yet, we know very little about how users’ perceived impediments affect a projects expected benefits in collaborative digital government initiatives. Using data from six public sector information-sharing projects, this paper reveals how some managerial and cultural impediments (e.g., control-oriented management) limit perceptions of expected benefits. Surprisingly, political impediments were not found to significantly affect the expectations of benefits. Additionally, the paper provides managers with specific advice on how to better understand users’ perceptions and expectations. The paper should be of interest to both academicians and practitioners who are interested in government information technology implementation, in general, and collaborative e-Government, in particular.

Implementing a Manufacturing Planning and Control Information System

Material Requirements Planning (MRP) and Manufacturing Resource Planning (MRP II) are computerized systems which replace traditional informal methods of manufacturing with formal planning and control procedures. They can provide improved customer service, improved materials management, and increased productivity. However, there have been numerous failures or near failures in implementing those systems. As a result, many companies have not received the full benefits from MRP/MRP II. The authors draw on feedback from a survey of 272 companies that have or are in the process of implementing MRP/MRP II to explain the determinants of a successful implementation. They also describe the implementation approach of one successful company to provide managers with additional insight into a successful implementation process.

The initiation and adoption of client-server technology in organizations

Abstract A large number of companies are adopting client–server systems. We investigated the relationship between several contextual factors and the initiation and adoption process of this important technology. The contextual factors included: (a) environmental, such as market position; (b) internal factors, namely organizational structure/culture, size, and migration strategy; and (c) technological, such as scope, scale, and cost of a system. An analysis of data from 350 companies revealed that a companys market position, its migration strategy, and the systems scope and scale have a significant effect on the initiation and adoption process.

A methodology for developing Bayesian networks: An application to information technology (IT) implementation

Abstract Bayesian Networks (BNs) are probabilistic inference engines that support reasoning under uncertainty. This article presents a methodology for building an information technology (IT) implementation BN from client–server survey data. The article also demonstrates how to use the BN to predict the attainment of IT benefits, given specific implementation characteristics (e.g., application complexity) and activities (e.g., reengineering). The BN is an outcome of a machine learning process that finds the network’s structure and its associated parameters, which best fit the data. The article will be of interest to academicians who want to learn more about building BNs from real data and practitioners who are interested in IT implementation models that make probabilistic statements about certain implementation decisions.

A Knowledge-Engineered System for Commercial Loan Decisions

M Recent financial applications of expert systems include: decision analysis in securities trading [1], cash flow analysis [12], and venture capital analysis for small telecommunication companies [4]. Another problem area that can benefit from this technology is commercial loan analysis, the process of evaluating a companys financial strengths and weaknesses. To correctly perform the analysis, commercial loan officers need to have an understanding of the primary Cs of lending: credit, collateral, capital, capacity, and character [13]. As commercial loan officers evaluate a company, they examine numerous financial ratios, percentages, and trends, and perform many interrelated analyses. Because the complex nature of the problem requires experience and precludes the use of simple algorithms, expert systems are appropriate for this type of loosely structured, complex problem. This article describes an expert system, Commercial Loan Analysis Support System (CLASS) [3]. The system uses rules and heuristics obtained from a com-

A strategic decision support system at Orell Fussli

Strategic decision support systems (strategic DSS) are one means of helping managers understand strategy and its implications. Strategic DSS contain many general decision support system (DSS) features, and are intended for senior managers. This article discusses the ongoing development of a strategic DSS for the Banknotes and Securities Division of Orell Fussli, a Swiss printing company. The system incorporates conceptual models, and provides explanations, cases, and guidance on how to use the models effectively. It helps train managers in strategic concepts and facilitates strategic thinking, and has been used to help develop and validate product/market strategies. We also provide several practical guidelines, including use of multiple conceptual models to present different perspectives and provision of a strategic management framework to organize those models. The systems features and guidelines add to our growing knowledge of how to electronically support strategic thinking.

Lending Analysis Support System (LASS): An Application of a Knowledge-Based System to Support Commercial Loan Analysis

Knowledge-based systems represent one of the most important and fastest growing research topics in the field of information and decision sciences. They promise to have an appreciable impact on decisionmaking in ill-structured decision settings where managers often employ semilogical procedures and tacit knowledge. The incorporation of knowledge engineering concepts with decision-support systems is discussed. A knowledge-based system supports the selection of appropriate models and data which are features contained in a conventional decisionsupport system. A knowledge-based prototype designed for the difficult problems encountered by commercial loan officers is also described, as are the elicitation and representation techniques employed in developing the prototype.

Client-server implementation: some management pointers

Using a sample of 350 companies, this paper investigates the benefits of client-server systems and links them to a set of implementation factors. The paper reveals that companies can expect competitive, operational, financial and technical benefits. It reports several important steps, activities and tasks that are positively related to those benefits, including defining clear organizational objectives and strategies, re-organizing corporate data and testing multiple levels of clients and servers. Furthermore, they list some of the problems that companies may encounter during a client-server implementation. The paper is relevant to managers and academicians who want to better understand the implementation of client-server.

Models for understanding the dynamics of organizational knowledge in consulting firms

Some consulting firms are implementing processes and technologies that transform individual experience into organizational knowledge, preserve it, and make it available to their employees. Advocates of knowledge management believe that these practices accelerate collective learning, improve competitiveness, and facilitate response to market changes. This paper uses a systems approach to understand knowledge management practices in the context of one prominent consulting firm. It incorporates influences that affect the firm and its ability to sustain knowledge, including staff departures, market shifts, and technological innovation. Knowledge managers must understand the dynamics imparted by these influences to ensure the future of the firm.

Acquiring expert rules with the aid of decision tables

This paper describes a computer-assisted approach to help knowledge engineers elicit rules from a domain expert. The approach uses the decision table as a knowledge engineering tool, and incorporates a decision table analyzer that displays rule conditions which can be used to query the expert. The decision table analyzer also reports redundant rules and provides assistance for developing rules that use as few variables as possible. This has the benefit of limiting the number of questions to be asked of the expert. The approach is especially suited for heuristic classification problems where evaluative judgments are based on many combinations of values of the same facts.