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Experienced fire ground commanders are known to make decisions in time-pressured and dynamic environments. The purpose of this paper is to report some of the tacit knowledge and skills expert firefighters use in performing complex fire ground tasks.

This study utilized a structured knowledge elicitation tool, known as the critical decision method (CDM), to elicit expert knowledge. Totally, 17 experienced firefighters were interviewed in-depth using a semi-structured CDM interview protocol. The CDM protocol was analysed using the emergent themes analysis approach.

Findings from the CDM protocol reveal both the salient cues sought, which the authors termed critical cue inventory (CCI), and the goals pursued by the fire ground commanders at each decision point. The CCI is categorized into five classes based on the type of information each cue generates to the incident commanders.

Since the CDM is a useful tool for identifying training needs, this study discussed the practical implications for transferring experts’ knowledge to novice firefighters.

Although many authors recognize that experts perform exceptionally well in their domains of practice, the difficulty still lies in getting a structured method for unmasking experts’ tacit knowledge. This paper is therefore relevant as it presents useful findings following a naturalistic knowledge elicitation study that was conducted across different fire stations in the UK and Nigeria.

This paper aims to explore the requirements of organizational knowledge management initiatives using requirements engineering techniques, identifying the optimal techniques configuration and serving as a management tool for knowledge engineers.

The method is selection attributes. Knowledge management enablers are characterized and mapped with the coverage capabilities of requirements engineering techniques, using the attributes of the elicited object and a box-plot analysis. The information is gathered from 280 references, 32 companies and 16 experts in requirements engineering.

Requirements of organizational knowledge management initiatives are got optimally by combining interviews, use cases, scenarios, laddering and focus group techniques. The requirements of structure and processes are more complex to identify, while culture requirements are the best covered.

Knowledge management enablers are analyzed according to the current studies and comprehension of engineering techniques.

Knowledge engineers need to consider the coverage capabilities of engineering techniques to design an optimal requirement identification and meet the objectives of organizational knowledge acquisition initiatives. Requirement engineers can improve the requirements identification by a staged selection process.

The requirements of knowledge management initiatives that impact the community can be identified and traced to ensure the knowledge objectives. Requirements related to culture and people, like shared values, beliefs, and behaviors, are also considered.

To the best of the authors’ knowledge, this is the first study about formal requirement identification of knowledge management initiatives in the organizational context, providing the optimal configuration. A novel staged process is proposed for requirements engineering techniques selection, analyzing the enablers at component level and identifying the attributes associated with the elicited object.

This paper aims to present a methodology for the mapping and evaluation of suppliers’ competencies and know-how. The authors operationalize the concept of organizational competence and provide companies with a customized management tool to map suppliers’ critical competencies for screening strategic from non-strategic suppliers and providing inputs for suppliers’ development.

Competencies assessment, carried out through a fuzzy knowledge management system (VINCI), is performed through the aggregation of indicators related to the control of critical resources, the degree of implementation of critical processes, the competitive positioning and the financial situation of a supplier. Competencies description and operationalization are based on the bottom-up elicitation of the subjective knowledge managers actually use to assess suppliers’ capability. Such subjective knowledge is then validated and formalized through a top-down approach based on strategic literature.

The authors tested VINCI on a sample of 38 suppliers of a large company. The results show that the methodology provides its users with a highly customizable knowledge map and its associated decision support tool that keeps into account the peculiar strategic needs of the company in the management of an existing portfolio of suppliers.

VINCI outcomes can be used to perform benchmarking analyses, define entry criteria and thresholds for suppliers’, identify improvement targets and service levels to be considered in the definition of supply contracts, supporting the alignment of supplier’s management with business strategy.

The most important original contribution of this work resides in the operationalization and measurements of firms’ competencies based on the elicitation of subjective knowledge that managers use in the actual assessment. A further distinctive feature of this paper is that the method is applied to small and medium companies, whereas large part of the literature on core or organizational competencies assessment is focused on large companies.

The purpose of this paper is to identify the appropriate method, demonstrating with a prototype model, of how knowledge in reliability management can be elicited from individuals as well as a team.

The approach is to elicit the tacit knowledge of the reliability engineers through narratives and cognitive mapping. With a sufficient number of cognitive maps, patterns are revealed and an aggregate cognitive map for all participating members is produced, which helps to summarize various approaches and procedures that can be taken in handling different reliability management issues.

The work provides a real‐life example to support the stages of learning from the individual, the group to the organizational level as described in the theoretical Learning Framework.

Many knowledge management programs failed for various reasons. One common pitfall is that they are either too ambitious or too vague in the scope, methodology of their deliverables. To be successful, the project objectives should be linked to the business needs that lead to solving their business problems.

A prototype is developed in the organization of expertise knowledge in a bottom‐up manner in the building of a corporate memory from individuals to team level in the reliability management in an airline company.

This is the first study in the airline industry to capture the know‐how and experience of its reliability engineers in the form of congregate cognitive maps so as to facilitate team learning and the building of organizational memory. It is the first in the airline industry to adopt this methodology for developing its own procedure manuals. The model was implemented successfully in the Engineering Division of an airline business in order to handle their reliability management issues.

The heavy civil engineering industry (railways, sewage treatment, chemical and pharmaceutical facilities, oil and gas facilities, etc.) is one of the major contributors to the British economy and generally involves a high level of investment. Clients in this industry are demanding accurate cost estimate, proper analysis of out‐turn cost and cost escalation and a high quality risk analysis throughout the construction processes. Current practice in the industry has suggested that there is a lack of structured methodologies and systematic cost escalation approach to achieve an appropriate cost analysis at the outset of projects and throughout the construction processes. In this context the prime objective of this research work is to develop a structured cost escalation methodology for improving estimating management and control in the heavy engineering industry construction processes. The methodology is composed of a forecasting model to predict cost indices of major items in industry and a risk knowledge base model for identifying and quantifying causes of cost escalations. This paper, as part of the research, reviews and discusses a knowledge‐based model for applying a cost escalation factor. The cost escalation factor is made up of market variation, a risk element and a component for bias. A knowledge elicitation strategy was employed to obtain the required knowledge for the model. The strategy included questionnaires, interviews and workshops and deliverables came in the form of influences and their effect on project cost escalation. From these deliverables, the concepts of a decision support model and system specification for applying cost escalation to base estimates is proposed.

The purpose of this paper is to propose an innovative approach for providing an answer to the emerging trends on how to integrate e‐learning efficiently in the business value chain in medium and large enterprises.

The proposed approach defines methodologies and technologies for integrating technology‐enhanced learning with knowledge and human resources management based on a synergistic use of knowledge models, methods, technologies and approaches covering different steps of the knowledge life‐cycle.

The proposed approach makes explicit and supports, from the methodological, technological and organizational points of view, mutual dependencies between the enterprise's organizational learning and the business processes, considering also their integration in order to allow the optimization of employees' learning plans with respect to business processes and taking into account competencies, skills, performances and knowledge available inside the organization.

This mutual dependency, bridging individual and organizational learning, enables an improvement loop to become a key aspect for successful business process improvement (BPI) and business process reengineering (BPR), enabling closure of, at the same time, the learning and knowledge loops at individual, group and organization levels.

The proposed improvements are relevant with respect to the state of the art and respond to a real need felt by enterprises and further commercial solutions and research projects on the theme.

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.

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.

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 for simple problems and worse for more difficult‐to‐model synthetic domains.

The findings suggest that it may be worth exploring some of the non‐traditional knowledge‐acquisition techniques when working on some types of applications. Further research could offer guidance in choosing the appropriate technique, with the aim of improving the quality, efficiency and development of the resulting system.

Designers of expert systems for marketing should consider interviewing and card sorting as the main means of knowledge acquisition for analytic problem domains, rather than protocol analysis as the main knowledge‐acquisition technique for analytic problem domains.

This paper is the first to suggest mapping between knowledge‐acquisition research and marketing problem domains.

This study/paper aims to study the knowledge audit methodologies needed in structured business processes (SBP) and unstructured business processes (UBP) respectively. The knowledge audit methodology used for SBP aims to identify and capture procedural knowledge, while the one for UBP aims to facilitate the sharing of experiential knowledge. The designs of audit methodologies, including elements of knowledge elicitation (KE), knowledge representation (KR), and role of researcher (RR) for SBP and UBP, are proposed in this paper.

Two knowledge audit cases studies were conducted. The first case was conducted in an SBP, and the second one in an UBP. The first case provides a view of a typical knowledge audit in SBP, the limitations are identified. The second case pinpoints the development of a new knowledge audit methodology applicable for UBP.

A significant differentiation between knowledge audits in SBP and UBP is that the knowledge to be captured in the former is procedural knowledge, whereas that to be elicited in the latter is experiential knowledge. The deliverables in the former include lists of knowledge workers, knowledge assets and knowledge inventories, and in the latter include the interplay of interaction between activities, stakeholders and knowledge displayed in the form of a knowledge activity network.

This research clarifies and strengthens the position of the knowledge audit by illustrating two knowledge audit methodologies for respective use in SBP and UBP. It points out that the fundamental difference of knowledge audit approaches is attributed to the different knowledge requirements. To cater to the different knowledge requirements, the authors asserted that three basic components of the knowledge audit, namely, KE, KR and the role of the researcher, should be customized.

Part 1 of this paper, published in the last issue of Property Management provided an overview of the research project currently being undertaken at the Polytechnic of Wales investigating the suitability of expert systems for the valuation of vacant possession residential properties for mortgage purposes. This paper will address some of the practical difficulties which developers of expert systems can expect to encounter, and offer a possible solution to the thorny problem of ‘domain appraisal’; ie, the investigation of a particular application to discover whether an expert system might be feasible.

Knowledge is a key driver for the competitive success of organizations, but about 90 percent of organizational knowledge is inside employees’ minds with personal essence; therefore, this paper provides valuable vision for managers by exploring knowledge acquisition (KA) techniques and personality type. The purpose of this paper is to examine KA techniques and explore the impact of personality type on the KA process in the aerospace industry.

This paper examines KA techniques through an empirical study involving 83 participants to take part in KA sessions. For exploring techniques, a questionnaire was used, and also the Myers-Briggs Type Indicator was used to identify participants’ personality type. The impact of personality type on KA processes was determined by correlation analysis.

Analyses confirmed some association between the type of personality and KA process. In addition, the findings of exploring questionnaire items showed that participants gave the laddering technique the highest rating.

The paper may be of high value to researchers in the field of KA, especially in aerospace industries, because there is very little experimental investigation of KA, and it also provides valuable information and guidelines that hopefully will help researchers to select appropriate KA techniques.