William P. Wagner

Selection of knowledge acquisition techniques based upon the problem domain characteristics of production and operations management expert systems

The application of expert systems to various problem domains in business has grown steadily since their introduction. Regardless of the chosen method of development, the most commonly cited problems in developing these systems are the unavailability of both the experts and knowledge engineers and difficulties with the process of acquiring knowledge from domain experts. Within the field of artificial intelligence, this has been called the ‘knowledge acquisition’ problem and has been identified as the greatest bottleneck in the expert system development process. Simply stated, the problem is how to acquire the specific knowledge for a well-defined problem domain efficiently from one or more experts and represent it in the appropriate computer format. Given the ‘paradox of expertise’, the experts have often proceduralized their knowledge to the point that they have difficulty in explaining exactly what they know and how they know it. However, empirical research in the field of expert systems reveals that certain knowledge acquisition techniques are significantly more efficient than others in helping to extract certain types of knowledge within specific problem domains. In this paper we present a mapping between these empirical studies and a generic taxonomy of expert system problem domains. In so doing, certain knowledge acquisition techniques can be prescribed based on the problem domain characteristics. With the production and operations management (P/OM) field as the pilot area for the current study, we first examine the range of problem domains and suggest a mapping of P/OM tasks to a generic taxonomy of problem domains. We then describe the most prominent knowledge acquisition techniques. Based on the examination of the existing empirical knowledge acquisition research, we present how the empirical work can be used to provide guidance to developers of expert systems in the field of P/OM.

Implementing corporate intranets: lessons learned from two high‐tech firms

Intranets are perhaps the hottest applications in the field of telecommunications today. The rapid growth of this application belies the fact that it has received little systematic study present in the academic literature. Presents two separate cases of corporate intranets that have been recently implemented. The focus of this report is to characterize the intranet implementations vis‐a‐vis the traditional systems development process. In so doing, an attempt is made to highlight the potential pitfalls through the lessons learned. As a starting‐point in the systematic study of intranets, a better definition is also introduced and a framework that captures and more accurately describes the wide variety of potential intranets.

The impact of problem domains and knowledge acquisition techniques: a content analysis of P/OM expert system case studies

Abstract In the past several decades, many expert system applications have been developed and reported in the literature. Case studies of these applications typically include a detailed description of the problem domain, knowledge acquisition techniques used and also some indication of the relative success of the application. This paper presents the results of an extensive content analysis of more than 90 expert system applications in the field of production and operations management. The content analysis presented here focuses on describing the knowledge acquisition techniques used and also on the problem domain that the applications address. For years developers have speculated that certain types of problems such as planning, are more difficult, but may yield a higher-impact system. Likewise, developers and empirical KA researchers have tried to determine the conditions under which certain KA techniques will work better than others. Researchers have also speculated for years about which techniques might work best for different problem domains. By carefully analyzing this large body of case studies and operationalizing the notion of the ‘impact’ of the expert system application, we can now begin to make normative conclusions about which techniques and which problem domains seem to yield applications that have the highest impact on the respective organization. This is also the first study that will offer more tangible evidence regarding the possible linkages between problem domains and KA techniques in a more pragmatic manner than has been done previously. In an environment of shrinking IT budgets, the results of this study can provide managers with real guidance about what projects may have the biggest potential impact on their organization.

A Conjoint Analysis of Voice Over IP Attributes

The ability to transmit and process voice over Internet protocol (VoIP) networks has important implications for technology managers. Many companies today are rushing to bring different VoIP products to market with a wide variety of features. Managers will need to understand the tradeoffs associated with VoIP as compared to the Public Switched Telephone Network (PSTN). This paper measures the preference structures between IP telephony and PSTN services using conjoint analysis. The purpose is to suggest those VoIP technology attributes that best meet users’ needs.

An analysis of the imagine PA public sector ERP project

We have seen organizations on a global scale continue to streamline their business processes enabled by enterprise resource planning (ERP) systems. Despite the recent economic downturn, the public sector represents one of the largest potential areas for new ERP sales. In addition the scale of public sector ERP projects is potentially huge as evidenced by the projected /spl divide/ for the US Navy ERP implementation and the US Army ERP implementation that is expected to include over 135,000 end users. The huge scale of these projects reinforces the need for successful ERP implementation methodologies for the public sector. Several governmental agencies in the US, Germany, Australia, and Malaysia have reported that the integration of agencies and systems in the public sector can be quite different from the private sector, requiring the use of a different approach and model. However, these agencies only attempted to implement different parts of an ERP system, whereas the US commonwealth or state of Pennsylvania is one of the first to attempt the integration of almost all of its governmental agencies with a single ERP package on a large scale. The question remains if there is a need to use a different enterprise systems implementation approach and model for a large-scale integrated ERP system in the public sector as compared to the private sector. This paper first identifies various differences in ERP implementation methodologies deployed in the public and private sectors, and then focuses on the issues and success factors of one large-scale public sector ERP project. Finally, these issues and success factors are compared to private sector ERP implementations.

Trends in expert system development

Diagnostic expert system applications continue to be the most popular.Synthetic type problem domains (such as design and planning) tend you yield higher impact systems.Rule-based knowledge representations tend you yield higher impact expert system applications.Unstructured interviews are not commonly used now for knowledge acquisition.In the past, structured and unstructured interviews tended to yield systems with equally high impact. Research in Expert Systems (ES) has been one of the longest-running, and most successful areas of ongoing research within the AI field. Since the 1980s, many case studies of ES applications have been published covering a wide range of functional areas and problem domains. These case studies contain an enormous amount of information about how ESs have been developed and how the tools, concepts, and applications have evolved since their inception. This research has painstakingly collected and analysed the content of 311 ES case studies dating from 1984 through 2016. A detailed content analysis was performed on this corpus in order to capture as many details as possible from each case. Further value was added to the study by using an impact scale to try and gauge the impact or success of the resulting application. With such a large sample size, the results are helpful in identifying how ES research has evolved and areas for further research.

The ImaginePA Project: The First Large-Scale, Public Sector ERP Implementation

Abstract While large-scale ERP deployments have been prevalent in the private-sector, there have been few attempts to deploy them in the public sector. This paper describes the first large-scale, public-sector ERP implementation, which integrates systems for over 50 different agencies in the state of Pennsylvania government. Over 20 individuals were interviewed during three years to identify and describe issues, success factors, implementation strategies, and lessons learned as compared to private-sector ERP implementations.

An experimental investigation of the impact of domain complexity on knowledge acquisition (KA) methods

This paper experimentally examines the effects of domain complexity on the quality of knowledge acquired and the efficiency with which knowledge acquisition (KA) is accomplished. The experiment is performed using two of the most prominent KA methods: unstructured interviews and protocol analysis. One contribution of the research is that it employs an experimental strategy that pays particular attention to addressing problematic issues of measurement and control. The experimental results indicate that domain complexity strongly influences the quality of knowledge acquired when protocol analysis is used for KA. While finding the other hypotheses to be inconclusive, some interesting trends were also identified regarding the quality and efficiency of knowledge acquisition methods.

Knowledge acquisition for marketing expert systems based upon marketing problem domain characteristics

Purpose – The purpose of this paper is to present various knowledge‐acquisition methods and to show how existing empirical research can be used for mapping between marketing problem domains and knowledge acquisition techniques. The key to doing this is to create a taxonomy of marketing problem domains.Design/methodology/approach – This paper combines a thorough literature review with prima facie conceptualization to map a generic problem domain, and thereby provide guidance in the choice of knowledge‐acquisition technique for developers of expert systems in the field of marketing.Findings – Recent empirical research in the field of expert systems shows that certain knowledge‐acquisition techniques are significantly more efficient than others for the extraction of certain types of knowledge within specific problem domains. It is found that protocol analysis, while fairly commonly used, is relatively inefficient for analytic problems. In the synthetic problem domain, interviewing proves to perform better fo...

An Analysis of Knowledge Acquisition Roles and Participants

Much recent research effort in the field of knowledge acquisition (KA) has focussed on extending knowledge acquisition techniques and processes to include a wider array of participants and knowledge sources in a variety of knowledge acquisition scenarios. As the domain of expert systems applications and research has expanded, techniques have been developed to acquire and incorporate knowledge from groups of experts and from various sources such as text, video, and audio tapes. However, the dominant participant-role model remains that of the knowledge engineer eliciting knowledge from one or more human experts. This conceptual gap has contributed to the major divisions in the KA field between researchers interested in manual KA and those developing tools for automated KA. This article considers the wide variety of possible KA scenarios and presents a meta-view of KA participants and the roles they may assume.We suggest that it is more appropriate to think of knowledge acquisition participants as playing one or more roles. These include knowledge sources, agents and targets for KA processes. We also present a participant model drawn from research in decision support systems that more accurately characterizes the diversity of the entities participating in the KA process. This view is more inclusive as it allows us to consider both human-human and human-computer KA interactions as well as the whole variety of knowledge sources and targets. A careful consideration of the meta-view and its associated role-participant mappings also yields the new ideas of the elemental and composite role and the multi-role entity. These new constructs are then used to identify areas where research is currently needed and to generate specific research issues. Taken altogether, this view allows a more flexible consideration of the many possible combinations that can and frequently do occur in actual KA situations.